Meal detection devices and methods

ABSTRACT

Devices and methods for detecting meal intake are disclosed herein. In some embodiments, one or more sensors can be used to detect or monitor physiological parameters of a user (e.g., heart rate, body movements, temperature, pH, impedance, gastric stretch, sound emissions, and the like). The outputs of the sensors can be received by a computer system configured to analyze the sensor data and make a determination as to whether meal intake has occurred or is presently occurring. The computer system&#39;s determination can be used to trigger, modulate, or otherwise control one or more therapeutic devices. Other types of devices can also be controlled using this determination, such as monitoring or logging devices.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims priority to U.S. Provisional Application No.61/780,013 filed on Mar. 13, 2013, which is hereby incorporated byreference herein in its entirety.

FIELD

Devices and methods for detecting meal intake are disclosed herein.

BACKGROUND

A number of therapies exist or are under development which can benefitfrom detection of meal intake with high sensitivity and/or highspecificity. For example, various obesity treatment therapies can bemore effective when administered in temporal proximity to or otherwisesynchronized with caloric ingestion (e.g., of solid or liquid foods orbeverages). Treatment therapies for diabetes and other diseases can alsobenefit from precise meal detection. Without the ability to accuratelydetect meal intake, automated therapies are difficult if not impossibleto implement.

Individuals or their caregivers can also benefit from an awareness ofmeal intake timing, patterns, and so forth. It is cumbersome and timeconsuming, however, to keep track of this information manually.

Accordingly, a need exists for accurate and reliable devices and methodsfor detecting meal intake.

SUMMARY

Devices and methods for detecting meal intake are disclosed herein. Insome embodiments, one or more sensors can be used to detect or monitorphysiological parameters of a user (e.g., heart rate, body movements,temperature, pH at one or more points along the gastrointestinal tract,impedance, gastric stretch, sound emissions, and the like). The outputsof the sensors can be received by a computer system configured toanalyze the sensor data and make a determination as to whether mealintake has occurred or is presently occurring. The computer system'sdetermination can be used to trigger, modulate, or otherwise control oneor more therapeutic devices. Other types of devices can also becontrolled using this determination, such as monitoring or loggingdevices.

In some embodiments, a meal detection system is provided that includes aplurality of sensors, each configured to sense a different physiologicalparameter of a user, the plurality of sensors being disposed external tothe user. The system can also include a processor in communication withthe plurality of sensors and configured to analyze outputs of theplurality of sensors to detect meal intake by the user, the processorbeing further configured to trigger a controlled device to deliver atherapy to the user in response to meal intake detected by theprocessor. In alternative embodiments, at least one of the sensors canbe at least partially disposed within the patient.

The plurality of sensors can be of different types. The processor can beconfigured, for each of the plurality of sensors, to calculate an indexbased on the output of the sensor and to determine that meal intakeoccurred when the index exceeds a threshold value. The processor can beconfigured to calculate the threshold value by processing a set oftraining data using an average harmonic mean algorithm, the trainingdata including sensor data for at least one user and ground truth datafor the at least one user.

The plurality of sensors can include an electromyograph configured todetect electrical activity of a muscle of the user and the processor canbe configured to calculate an electromyograph index based on a number ofpeaks detected in the electromyograph output. The plurality of sensorscan include a microphone configured to detect sounds emitted by the userand the processor can be configured to calculate a microphone indexbased on frequency matching and temporal matching of the microphoneoutput to a predetermined pattern. The plurality of sensors can includean electrocardiograph configured to detect electrical activity of aheart of the user and the processor can be configured to calculate anelectrocardiograph index based on a moving average filtered firstderivative of the standard deviation of interbeat intervals in theelectrocardiograph output.

The plurality of sensors can include a temperature sensor configured todetect a temperature of the user and the processor can be configured tocalculate a temperature sensor index based on a ratio of low frequencycomponents of the first derivative of the temperature sensor output tolow frequency components of the standard deviation of the temperaturesensor output. The plurality of sensors can include an accelerometerconfigured to detect motion of the user and the processor can beconfigured to calculate an accelerometer index based on the total energyof the accelerometer output in a frequency band of interest. Theplurality of sensors can include an electrogastrograph configured todetect electrical activity of a digestive system of the user and theprocessor can be configured to calculate an electrogastrograph indexbased on the total energy of the electrogastrograph output in afrequency band of interest. The plurality of sensors can include animpedance sensor configured to detect an impedance across a portion ofthe user and the processor can be configured to calculate an impedancesensor index based on the median energy of the impedance sensor outputin a frequency band of interest.

The plurality of sensors can include an electromyograph and anaccelerometer, and the processor can be configured to calculate anelectromyograph index, an electromyograph threshold value, anaccelerometer index, and an accelerometer threshold value. The processorcan be configured to determine that solid meal intake occurred when theelectromyograph index exceeds the electromyograph threshold value, thatliquid meal intake occurred when the electromyograph index does notexceed the electromyograph threshold value and the accelerometer indexexceeds the accelerometer threshold value, and that no meal intakeoccurred when the electromyograph index does not exceed theelectromyograph threshold value and the accelerometer index does notexceed the accelerometer threshold value.

The plurality of sensors can include an impedance sensor and anaccelerometer, and the processor can be configured to calculate animpedance sensor index, an impedance sensor threshold value, anaccelerometer index, and an accelerometer threshold value. The processorcan be configured to determine that solid meal intake occurred when theimpedance sensor index exceeds the impedance sensor threshold value,that liquid meal intake occurred when the impedance sensor index doesnot exceed the impedance sensor threshold value and the accelerometerindex exceeds the accelerometer threshold value, and that no meal intakeoccurred when the impedance sensor index does not exceed the impedancesensor threshold value and the accelerometer index does not exceed theaccelerometer threshold value.

The plurality of sensors can include an electromyograph and amicrophone, and the processor can be configured to calculate anelectromyograph index, an electromyograph threshold value, a microphoneindex, and a microphone threshold value. The processor can be configuredto determine that solid meal intake occurred when the electromyographindex exceeds the electromyograph threshold value, that liquid mealintake occurred when the electromyograph index does not exceed theelectromyograph threshold value and the microphone index exceeds themicrophone threshold value, and that no meal intake occurred when theelectromyograph index does not exceed the electromyograph thresholdvalue and the microphone index does not exceed the microphone thresholdvalue.

The plurality of sensors can include an impedance sensor and amicrophone, and the processor can be configured to calculate animpedance sensor index, an impedance sensor threshold value, amicrophone index, and a microphone threshold value. The processor can beconfigured to determine that solid meal intake occurred when theimpedance sensor index exceeds the impedance sensor threshold value andthe microphone index exceeds the microphone threshold value, that liquidmeal intake occurred when the impedance sensor index does not exceed theimpedance sensor threshold value and the microphone index exceeds themicrophone threshold value, and that no meal intake occurred when theimpedance sensor index does not exceed the impedance sensor thresholdvalue and the microphone index does not exceed the microphone thresholdvalue.

The system can include a controlled device configured to perform variousfunctions. The controlled device can be configured to at least one of:electrically stimulate tissue of the user, deliver a therapeutic agentto the user, deliver a therapeutic agent configured to provoke a releaseof one or more hormones from L-cells of the user to trigger ileal brakein the user, deliver insulin to the user, modulate bile acid levels inthe user, modulate gastric pH levels in the user, induce an aversiveresponse in the user, stimulate release of GLP-1 in the user, activatebrown adipose tissue in the user, adjust a gastric band implanted in theuser, control tonal contractions of the user's stomach, adjust a size orvolume of a gastric space occupying device implanted in the user,modulate gastric emptying in the user, record a history of the user'smeal intake events, and issue an alert to the user or to a caregiver ofthe user when the user's meal intake exceeds a predetermined thresholdor deviates from a predetermined pattern.

In some embodiments, a medical method is provided that includes sensinga plurality of physiological parameters of a user using a plurality ofsensors disposed externally to the user and, using a processor incommunication with the plurality of sensors, analyzing outputs of theplurality of sensors to detect meal intake by the user. The method caninclude automatically triggering a controlled device to deliver atherapy to the user in response to meal intake detected by theprocessor. The delivery of the therapy can be configured to commencewith the initiation of the meal, the end of the meal, or at apredetermined time after the start or end of the meal.

The method can include, for each of the plurality of sensors, using theprocessor to calculate an index based on the output of the sensor andusing the processor to determine that meal intake occurred when theindex exceeds a threshold value. The method can include using theprocessor to calculate the threshold value by processing a set oftraining data using an average harmonic mean algorithm, the trainingdata including sensor data for at least one user and ground truth datafor the at least one user.

Said sensing and said analyzing can include at least one of: detectingelectrical activity of a muscle of the user using an electromyograph andcalculating an electromyograph index based on a number of peaks detectedin the electromyograph output, detecting sounds emitted by the userusing a microphone and calculating a microphone index based on frequencymatching and temporal matching of the microphone output to apredetermined pattern, detecting electrical activity of a heart of theuser using an electrocardiograph and calculating an electrocardiographindex based on a moving average filtered first derivative of thestandard deviation of interbeat intervals in the electrocardiographoutput, detecting a temperature of the user and calculating atemperature sensor index based on a ratio of low frequency components ofthe first derivative of the temperature sensor output to low frequencycomponents of the standard deviation of the temperature sensor output,detecting motion of the user using an accelerometer and calculating anaccelerometer index based on the total energy of the accelerometeroutput in a frequency band of interest, detecting electrical activity ofa digestive system of the user using an electrogastrograph andcalculating an electrogastrograph index based on the total energy of theelectrogastrograph output in a frequency band of interest, and detectingan impedance across a portion of the user using an impedance sensor andcalculating an impedance sensor index based on the median energy of theimpedance sensor output in a frequency band of interest.

Triggering the controlled device can include causing the controlleddevice to at least one of: electrically stimulate tissue of the user,deliver a therapeutic agent to the user, deliver a therapeutic agentconfigured to provoke a release of one or more hormones from L-cells ofthe user to trigger ileal brake in the user, deliver insulin to theuser, modulate bile acid levels in the user, modulate gastric pH levelsin the user, induce an aversive response in the user, stimulate releaseof GLP-1 in the user, activate brown adipose tissue in the user, adjusta gastric band implanted in the user, control tonal contractions of theuser's stomach, adjust a size or volume of a gastric space occupyingdevice implanted in the user, modulate gastric emptying in the user,record a history of the user's meal intake events, and issue an alert tothe user or to a caregiver of the user when the user's meal intakeexceeds a predetermined threshold or deviates from a predeterminedpattern.

Sensing the plurality of physiological parameters can include detectingan impedance across a portion of the user using an impedance sensorhaving a first current electrode, a second current electrode, a firstvoltage electrode, and a second voltage electrode. The method caninclude positioning the first current electrode on the user's lefttrapezius muscle, positioning the second current electrode on the user'sright trapezius muscle, positioning the first voltage electrode on theuser's chest below the user's left clavicle and about half way betweenthe user's neck and the user's left shoulder, and positioning the secondvoltage electrode on the user's chest below the user's right clavicleand about half way between the user's neck and the user's rightshoulder. Alternatively, or in addition, the method can includepositioning the first current electrode on the user's chest below theuser's left clavicle and about half way between the user's neck and theuser's left shoulder, positioning the second current electrode on theuser's chest below the user's right clavicle and about half way betweenthe user's neck and the user's right shoulder, positioning the firstvoltage electrode beneath the first current electrode and inward towardsthe user's sternum, and positioning the second voltage electrode beneathsecond current electrode and inward towards the user's sternum.

The present invention further provides devices and methods as claimed.

BRIEF DESCRIPTION OF THE DRAWINGS

The invention will be more fully understood from the following detaileddescription taken in conjunction with the accompanying drawings, inwhich:

FIG. 1 is a schematic diagram of a controlled device and a mealdetection system having a plurality of sensors coupled to a user;

FIG. 2 is a schematic diagram of a computer system of the meal detectionsystem of FIG. 1;

FIG. 3A is an exemplary protocol for use in obtaining training data forcalibrating the meal detection system of FIG. 1;

FIG. 3B is another exemplary protocol for use in obtaining training datafor calibrating the meal detection system of FIG. 1;

FIGS. 4A-4G illustrate an exemplary method of calculating an index foran electromyograph;

FIGS. 5A-5D illustrate an exemplary method of calculating an index for amicrophone;

FIGS. 6A-6C illustrate an exemplary method of calculating an index foran electrocardiograph;

FIGS. 7A-7E illustrate an exemplary method of calculating an index for atemperature sensor;

FIGS. 8A-8E illustrate an exemplary method of calculating an index foran accelerometer;

FIGS. 9A-9C illustrate an exemplary method of calculating an index foran electrogastrograph;

FIGS. 10A-10B illustrate an exemplary method of calculating an index foran impedance sensor;

FIGS. 11A-11F illustrate exemplary placements of impedance sensorelectrodes on a patient;

FIG. 12 is a table of sensitivity and specificity for various sensorsand meal categories;

FIG. 13 is a table of sensitivity and specificity for various sensorcombinations and meal categories;

FIG. 14 is a schematic diagram of a controlled device for administeringelectrical stimulation to a user;

FIG. 15 is a side view of a controlled device for administering atherapeutic agent to a user, the device being shown implanted in theuser;

FIG. 16 is a perspective view of a reservoir portion of the controlleddevice of FIG. 15; and

FIG. 17 is a perspective view of a catheter portion of the controlleddevice of FIG. 15.

DETAILED DESCRIPTION

Certain exemplary embodiments will now be described to provide anoverall understanding of the principles of the structure, function,manufacture, and use of the devices and methods disclosed herein. One ormore examples of these embodiments are illustrated in the accompanyingdrawings. Those of ordinary skill in the art will understand that thedevices and methods specifically described herein and illustrated in theaccompanying drawings are non-limiting exemplary embodiments and thatthe scope of the present invention is defined solely by the claims. Thefeatures illustrated or described in connection with one exemplaryembodiment may be combined with the features of other embodiments. Suchmodifications and variations are intended to be included within thescope of the present invention.

INTRODUCTION

Devices and methods for detecting meal intake are disclosed herein. Insome embodiments, one or more sensors can be used to detect or monitorphysiological parameters of a user (e.g., heart rate, body movements,temperature, pH at one or more points along the gastrointestinal tract,impedance, gastric stretch, sound emissions, and the like). The outputsof the sensors can be received by a computer system configured toanalyze the sensor data and make a determination as to whether mealintake has occurred or is presently occurring. The computer system'sdetermination can be used to trigger, modulate, or otherwise control oneor more therapeutic devices. Other types of devices can also becontrolled using this determination, such as monitoring or loggingdevices.

Such devices and methods can be used to trigger automated or manualtherapies for treating a user. In some embodiments, therapy can beadministered to the user for a limited period of time such that the userstops receiving the therapy prior to a second onset of meal intake,e.g., the user beginning a second eating session, which can trigger asecond delivery of the therapy to the user for a limited period of time.In other words, the user can intermittently receive therapy throughout aperiod of hours, days, weeks, months, etc., with each delivery of thetherapy coinciding with meal intake. By providing therapy in conjunctionwith eating and/or drinking, the therapy can be most effective intreating a user condition and/or encouraging weight loss. Accurate mealdetection provided by such devices and methods can be an importantbaseline prerequisite for automated or semi-automated therapies,including obesity and insulin treatment therapies, as well as others.Therapies for metabolic disorders can also be more effective ifcoordinated with meal intake.

References herein to “meal ingestion” or “meal intake” can includeingestion of solid foods, liquid foods, beverages, snacks, and so forth,whether caloric or otherwise.

System Generally

FIG. 1 illustrates an exemplary embodiment of a meal detection system100 for detecting meal intake by a user 102. The system 100 generallyincludes one or more sensors 104 configured to sense physiologicalparameters of the user 102 and a computer system 106 configured toprocess and interpret the outputs of the one or more sensors to make adetermination as to whether meal intake has occurred or is presentlyoccurring. Each sensor 104 can monitor different physiologicalparameters of the user. A controlled device 108 can be coupled to themeal detection system 100 such that the meal detection system isconfigured to trigger, modulate, or otherwise control the controlleddevice 108 based on determinations made by the computer system 106.

The sensors 104, the computer system 106, and the controlled device 108can all be implanted within the user 102, can all be positioned externalto the user, or some can be implanted while others are positionedexternally. For example, some components can be positionedsubcutaneously while others are positioned transcutaneously. Componentsof the system which are implanted can be powered using an implantedpower source or can be powered remotely, for example as disclosed inU.S. Pat. No. 7,599,743 filed Jun. 24, 2004 entitled “Low FrequencyTranscutaneous Energy Transfer To Implanted Medical Device.” Thecomputer system 106 can be configured for implantation in the user, forexample by including a hermetically-sealed biocompatible coating. Thecomputer system 106 can also be configured to be worn or carried by theuser, for example by integrating the computer system 106 with an articleof clothing or other accessory. The computer system 106 can be, or canbe included in, a portable computer, a desktop computer, a handheldelectronic device such as a mobile phone, etc., as will be appreciatedby a person skilled in the art. It will be appreciated that anycombination of the sensors 104, the computer system 106, and thecontrolled device 108 can be integrated into a single physical device,housing, package, or system.

The computer system 106 can be directly coupled to the sensors 106 andthe controlled device 108, e.g., using electrically-conducive wires orleads, or can be wirelessly coupled thereto using various protocolsknown in the art. Sensor data can be transmitted to the computer system106 in real time. The computer system 106 can also be configured to sendinstructions to the sensors 104, for example to reset or calibrate thesensors, or to instruct the sensors to take a measurement.

Computer System

FIG. 2 illustrates an exemplary architecture of the computer system 106.Although an exemplary computer system 106 is depicted and describedherein, it will be appreciated that this is for sake of generality andconvenience. In other embodiments, the computer system may differ inarchitecture and operation from that shown and described here. Forexample, a system on chip (SOC) architecture can be used to decrease thesize of the computer system and increase its portability and/orimplantability.

The illustrated computer system 106 includes a processor 202 whichcontrols the operation of the computer system 106, for example byexecuting an operating system (OS), device drivers, applicationprograms, and so forth. The processor 202 can include any type ofmicroprocessor or central processing unit (CPU), including programmablegeneral-purpose or special-purpose microprocessors and/or any of avariety of proprietary or commercially-available single ormulti-processor systems. The computer system 106 also includes a memory204, which provides temporary or permanent storage for code to beexecuted by the processor 202 (e.g., programs being configured to causethe computer system 106 to perform one or more steps) or for data thatis processed by the processor 202. The memory 204 can include read-onlymemory (ROM), flash memory, one or more varieties of random accessmemory (RAM), and/or a combination of memory technologies. The variouselements of the computer system 106 are coupled to a bus system 206. Theillustrated bus system 206 is an abstraction that represents any one ormore separate physical busses, communication lines/interfaces, and/ormulti-drop or point-to-point connections, connected by appropriatebridges, adapters, and/or controllers.

The computer system 106 also includes a network interface 208, aninput/output (I/O) interface 210, a storage device 212, and a displaycontroller 214. The network interface 208 enables the computer system106 to communicate with remote devices (e.g., other computer systems)over a network. The I/O interface 210 facilitates communication betweenone or more input devices (e.g., the sensors 104), one or more outputdevices, and the various other components of the computer system 106.The storage device 212 can include any conventional medium for storingdata and programs in a non-volatile and/or non-transient manner. Thestorage device 212 can thus hold data and/or instructions in apersistent state (i.e., the value is retained despite interruption ofpower to the computer system 106). The storage device 212 can includeone or more hard disk drives, flash drives, USB drives, optical drives,various media disks or cards, and/or any combination thereof and can bedirectly connected to the other components of the computer system 106 orremotely connected thereto, such as over a network. The displaycontroller 214 includes a video processor and a video memory, andgenerates images to be displayed on one or more displays in accordancewith instructions received from the processor 202.

The various functions performed by the meal detection system 100 can belogically described as being performed by one or more modules. It willbe appreciated that such modules can be implemented in hardware,software, or a combination thereof. It will further be appreciated that,when implemented in software, modules can be part of a single program orone or more separate programs, and can be implemented in a variety ofcontexts (e.g., as part of an operating system, a device driver, astandalone application, and/or combinations thereof). In addition,software embodying one or more modules can be stored as an executableprogram on one or more non-transitory computer-readable storage mediums.Functions disclosed herein as being performed by a particular module canalso be performed by any other module or combination of modules, and themeal detection system 100 can include fewer or more modules than what isshown and described herein.

It will be appreciated that sensor data can be communicated to thecomputer system 106 instantaneously or near-instantaneously. Thecomputer system 106 can thus analyze relatively recent data andrelatively quickly begin analysis thereof, as will be appreciated by aperson skilled in the art. In this way, the computer system 106 can makea relatively quick determination as to whether the user has beguningesting a meal. This in turn can be used to trigger the controlleddevice 108 in a relatively quick manner. In other words, if the computersystem 106 determines from the gathered data that the user startedingesting a meal, delivery of a therapy to the user can be automaticallyinitiated relatively soon after the onset of meal intake.

The computer system 106 can perform various signal processing functionswith respect to the sensor data to make the data more suitable for mealintake determinations or for calculating a measurement index forassessing whether meal intake has likely occurred, e.g., as detailedbelow with respect to each sensor type. The computer system 106 caninclude a meal intake determination module configured to make adetermination as to whether meal intake has occurred or is presentlyoccurring. The meal intake determination module can also be configuredto determine or estimate the size of the meal, for example based on thesignal count or pattern of one or more sensor outputs, e.g., anelectromyograph, an impedance sensor, and/or an accelerometer. Any of avariety of algorithms can be used to make the meal intake determinationbased on sensor data received by the computer system 106.

In some embodiments, the determination algorithm can include comparingan index value calculated for a particular sensor over a particularwindow of time to a predetermined threshold value. Index values for aplurality of sensors can also be considered together in making the mealintake determination. Further details on determination algorithms areprovided below.

Sensors

Generally, the sensors 104 can be configured to gather data from theuser 102 regarding one or more physiological parameters of the user, andeach sensor typically gathers data for a different physiologicalparameter. The sensors 102 can be in communication with the computersystem 106 such that the sensors communicate sensed data to the computersystem 106 for processing. A number of exemplary sensors are describedbelow.

An externally-located sensor can allow for meal detection and therapytriggering without requiring surgery to implant the sensor, therebyreducing, if not eliminating, adverse side effects and potentialcomplications from surgery. If a controlled device configured to betriggered based on data gathered by an externally-located sensor is alsotranscutaneously positioned, e.g., in the form of a transdermal patchconfigured to electrically stimulate the user, then the user can beeffectively treated without requiring any surgery, thereby eliminatingadverse side effects and potential complications from surgery. However,it will be appreciated that the sensors 104 can also be implanted in theuser as part of a surgical procedure (e.g., a surgical procedure totreat severe obesity).

A plurality of sensors can be used simultaneously to inform the mealintake determination, providing redundancy in case of sensor and/orcommunication failure, and increasing accuracy in determining that mealintake has occurred or is occurring. For example, sensor combinationscan be used in which one sensor is very effective at detecting one typeof activity (e.g., eating solid food) and another sensor is veryeffective at detecting a different type of activity (e.g., drinking orexercise) such that the combination of sensors provides a synergisticimprovement in meal detection accuracy.

In some embodiments, a measurement index can be calculated for eachsensor or for each sensor type and can be compared to a threshold valueto inform a meal intake determination. While a number of exemplary indextypes and threshold values are disclosed below, it will be appreciatedthat other index types or threshold values can be used depending on theparticular application and its sensitivity and specificity requirementsand other factors.

Threshold values can be determined empirically by monitoring one or moresubjects as they perform various activity protocols. Exemplary protocolsare illustrated in FIGS. 3A and 3B. Sensor data can be captured duringthe protocols along with an individual ground truth for each subject(e.g., a log of when the subject is actually chewing, swallowing, ordigesting). This training data can be divided into a plurality of timesegments (e.g., segments of 5 minutes each). The number of truepositives (TP), true negatives (TN), false positives (FP), and falsenegatives (FN) can be calculated, along with the equivalent sensitivity(TP/(TP+FN)) and specificity (TN/(TN+FP)). A sensitivity value SE(n, T)and specificity value SP(n, T) can be determined for each possiblethreshold value T and for each subject n in the training set. An averageharmonic mean of the sensitivity and specificity can be calculated todetermine an ideal threshold value for the sensor that optimizesspecificity and sensitivity. Average harmonic mean of sensitivity SE(n,T) and specificity SP(n, T) can be calculated according to:

${{H(T)} = {\frac{1}{N}{\sum\limits_{n = 1}^{N}\; \frac{2 \cdot {{SE}\left( {n,T} \right)} \cdot {{SP}\left( {n,T} \right)}}{{{SE}\left( {n,T} \right)} + {{SP}\left( {n,T} \right)}}}}},$

where n represents the subject index, T is the determination thresholdvalue, and N is the number of subjects in the training set. The maximumvalue of T in the function H(t) can be used as the determinationthreshold for the sensor. Threshold values for each sensor type can bedetermined empirically and stored in the memory 204 of the computersystem 106 during manufacturing for subsequent use with all users of thesystem 100.

Alternatively, or in addition, user-specific thresholds can be used. Forexample, a training set can consist solely of the individual end-user ofthe meal detection system 100. The meal detection system 100 can thus beoperable in a training mode in which sensor data is recorded and theuser provides ground truth information to the computer system 106 (e.g.,by manually signaling to the meal detection system 100 when meal intakeis occurring, and optionally the type and volume of the meal intake).This information can be used by the computer system 106 as describedabove to define thresholds for each sensor that are tailored to theindividual user. Later, when the meal detection system 100 is no longeroperating in the training mode, these thresholds can be used toautomatically detect meal intake without requiring additional userinput. Reference is made herein to various sensor outputs or indexes“exceeding” a threshold. It will be appreciated that “exceeding” athreshold can, in some instances, be understood to mean crossing athreshold. In other words, a value that is numerically less than athreshold value can be considered to “exceed” the threshold when thethreshold is defined such that values which are numerically less thanthe threshold are considered a trigger. For example, if a threshold isdefined as “trigger when less than 7,” then a value of 3 can be said to“exceed” the threshold.

Electromyographs (EMG)

The one or more sensors 104 can include an electromyograph (“EMG”)configured to sense or detect electrical potential of one or more of theuser's muscles. The electromyograph can generate an output signal thatrepresents the muscle's electrical potential as a function of time. Theelectromyograph can include surface leads or electrodes configured forattachment to the user's skin and/or intramuscular leads or electrodesconfigured to be placed within the observed muscles, e.g., in the formof needles or wires. In some embodiments, the electromyograph can have asampling rate of about 312.5 Hz. Exemplary electromyographs include theBiopac MP150 Data Acquisition System and the Biopac 100C BiopotentialAmplifier available from Biopac Systems, Inc.

The electromyograph electrodes can be coupled to, or configured tomeasure, various muscles or muscle groups of the user. For example, asshown in FIG. 1, the electromyograph electrodes 110 can be coupled tothe user's jaw muscles (e.g., the masseter, the temporalis, thesphenomandibularis, the medial pterygoid, the lateral pterygoid, thehyoid, and/or the sternohyomastoid). Alternatively, or in addition, theelectromyograph electrodes can be coupled to other muscles, such as theuser's neck muscles or abdominal muscles. Each time the monitoredmuscles are fired (e.g., the jaw muscles when chewing food), a peak canbe generated in the electromyograph output. Information representing thenumber of peaks that occur in a certain period of time or theamplitude/intensity of the peaks can be used for meal detectionpurposes.

The electromyograph output can be received by the computer system 106and can be conditioned and otherwise processed to detect meal intake bythe user. FIG. 4A illustrates an exemplary raw output signal generatedby the electromyograph and communicated to the computer system 106. Thecomputer system 106 can analyze the sensor output in segments thatcorrespond to discrete windows of time. For example, the computer system106 can record the sensor output for a predetermined time period (e.g.,10 seconds, 30 seconds, 1 minute, 5 minutes, 10 minutes, etc.) and, atthe conclusion of the predetermined time period or thereafter, analyzethe sensor output corresponding to that time period.

The computer system 106 can perform envelope extraction to produce anestimated superior envelope of the raw electromyograph signal for thetime period under consideration, as shown in FIG. 4B. The computersystem 106 can then perform peak detection (FIG. 4C) and event density(FIG. 4D) processing. As shown in FIG. 4E, the computer system 106 canextract a chewing phase from the processed data. Chewing episodesassociated with meal intake are typically characterized by multiple,rhythmic chewing events. Accordingly, spurious chewing episodes, shownin FIG. 4F, can be excluded from the data using an index that is theratio of the number of detected peaks to the variance of the inter-peakintervals.

Time periods in which the electromyograph output produces an index valuebelow the threshold amount can be excluded as not involving meal intake.Thus, as shown in FIG. 4G, the spurious chewing events of FIG. 4F can beignored. Time periods in which the electromyograph output produces anindex values greater than or equal to the threshold can be interpretedas meal intake by the user or, as discussed below, can be used inconjunction with other data to make such an interpretation. In someembodiments, the threshold index value can be about 43. Accordingly,peak-detection based processing can be used to detect chewing eventsfrom the electromyograph output.

Microphones

The one or more sensors can include a microphone configured to sense ordetect sounds generated or emitted by the user. A variety of microphonetypes can be used, including condenser microphones, dynamic microphones,ribbon microphones, carbon microphones, piezoelectric microphones, fiberoptic microphones, laser microphones, liquid microphones, and MEMSmicrophones. The microphone can include an acoustic-to-electrictransducer that converts sounds generated by the user into an electricaloutput signal.

The microphone transducer can be configured for attachment to the user'sskin or clothing, or can be implanted in the user. In some embodiments,the microphone can have a sampling rate of about 44,100 Hz. Exemplarymicrophones include the NT3 Throat Microphone System available fromIASUS Concepts Ltd.

The microphone can coupled to, aimed at, or disposed in proximity tovarious portions of the user. For example, as shown in FIG. 1, a firstmicrophone 112 can be coupled to the user's throat and a secondmicrophone 114 can be coupled to the user's abdomen in the vicinity ofthe user's stomach. The first microphone can detect sounds emitted bythe user's throat when the user is swallowing. The second microphone candetect sounds emitted by the user's gastrointestinal system as food orbeverages are digested. When such sounds are detected, a signaturepattern can be generated in the microphone output. Informationrepresenting the number of patterns that occur in a certain period oftime or the amplitude/intensity of the patterns can be used for mealdetection.

The microphone output can be received by the computer system 106 and canbe conditioned and otherwise processed to detect meal intake by theuser. The computer system 106 can analyze the microphone output insegments that correspond to discrete windows of time. For example, thecomputer system 106 can record the microphone output for a predeterminedtime period (e.g., 10 seconds, 30 seconds, 1 minute, 5 minutes, 10minutes, etc.) and, at the conclusion of the predetermined time periodor thereafter, analyze the microphone output corresponding to that timeperiod.

FIG. 5A is time-frequency spectrogram that exemplifies the output of athroat microphone during a period that includes plural swallowingevents, shown with a corresponding ground truth plot. As shown, adiscernable pattern coincides with each swallowing event. In theillustrated embodiment, the pattern is characterized by short durationepisodes of a large frequency band. The computer system 106 can performvarious signal processing routines to condition the raw microphoneoutput. For example, notch filters can be used to eliminate noise in aparticular frequency band and its harmonics. A non-linear spatial filtercan be used to make the frequency pattern more pronounced. A spectrogramapplied to the filtered output can be normalized to diminish the effectof residual noise, for example by normalizing the power over the entirespectrogram.

In some embodiments, swallowing events can be extracted using acombination of frequency and temporal pattern recognition. The processedspectrogram described above can be used to compute temporal gradientvalues. The correlation between the obtained temporal gradient valuesand a template characterized by consecutive positive, null, and negativegradient values can be computed over the entire recording. FIG. 5Billustrates an exemplary template and the resulting matching score foran exemplary sensor output. Speech episodes can be rejected by computinglocal power spectral densities (PSD) and testing for correlation withPSD templates of swallowing (SW), speaking (SP), and ambient (AMB)episodes, respectively, as shown in FIG. 5C. Template and binarizedscores can be obtained by computing the template/processed spectrogramcorrelation for each sampling time. Maximum correlation valuesassociated with the swallowing pattern can be scored as “1” while indexvalues of “0” can be assigned otherwise. The frequency and temporalscores can then be multiplied to obtain a final index value. FIG. 5Dschematically illustrates the complete processing scheme.

In other words, a first score can be obtained by performing frequencypattern matching and a second score can be obtained by performingtemporal pattern matching. The product of the spectral score and thetemporal score can be used as a detection threshold index. Microphonerecordings with index values below the threshold amount can be excludedas not involving meal intake. Microphone recordings with index valuesgreater than or equal to the threshold can be interpreted as meal intakeby the user or, as discussed below, can be used in conjunction withother data to make such an interpretation. In some embodiments, thethreshold index value for a throat or larynx microphone can be about5.5. It will be appreciated that similar techniques can be used toobtain threshold values for microphones directed at other portions ofthe user, such as the user's stomach. Accordingly, a combination offrequency and temporal pattern matching can be used to detect swallowingevents from the output of a throat microphone.

Electrocardiographs (ECG)

The one or more sensors can include an electrocardiograph (“ECG”)configured to sense or detect electrical activity of the user's heart.The electrocardiograph can generate an output signal that represents theheart's electrical activity as a function of time. Theelectrocardiograph can include surface leads or electrodes configuredfor attachment to the user's skin and/or implantable leads or electrodesconfigured to be placed within the user's body. In some embodiments, theelectrocardiograph can have a sampling rate of about 321.25 Hz.Exemplary electrocardiographs include the SEN3—Sense V2 System availablefrom CSEM.

The electrocardiograph electrodes can be coupled to the user at avariety of locations. For example, as shown in FIG. 1, theelectrocardiograph electrodes 116 can be coupled to the user's thorax ortrunk at a plurality of locations. The electrocardiograph output can beused to determine the user's heart rate and to detect changes in theuser's heart rate (e.g., heart rate variability (HRV)). The computersystem 106 can analyze the electrocardiograph output and determinewhether the HRV indicates an onset of the user ingesting food or drink.

Changes in heart rate can occur after ingestion, as discussed forexample in Friesen et al., “Autonomic Nervous System Response To A SolidMeal And Water Loading In Healthy Children: Its Relation To GastricMyoelectrical Activity,” Neurogastroenterol Motil. 19(5): 376-382(2007); Friesen et al., “The Effect Of A Meal And Water Loading On HeartRate Variability In Children With Functional Dyspepia,” Dig Dis Sci 55:2283-2387 (2010); Yin et al., “Inhibitory Effects Of Stress OnPostprandial Gastric Myoelectrical Activity And Vagal Tone In HealthySubjects,” Neurogastroenterol Motil 16(6): 737-744 (December 2004);Watanabe et al., “Effects of water ingestion on gastric electricalactivity and heart rate variability in healthy subjects,” J Auton NeuroSyst 58(1-2): 44-50 (1996); and Lipsitz et al., “Hemodynamic AndAutonomic Nervous System Responses To Mixed Meal Ingestion In HealthyYoung And Old Subjects And Dysautonomic Patients With PostprandialHypotension,” Circulation, 87: 391-400 (1993).

HRV analysis can be performed in a variety of ways, such as usingtime-domain and/or frequency-domain methods, as will be appreciated by aperson skilled in the art. Generally, the time-domain methods caninclude calculations directly from raw R-R interval time series data,e.g., raw data of times from the peak of one R to the next R peak in aQRS complex of an echocardiogram, such as by using the standarddeviation of all normal R-R intervals (SDNN), the standard deviation ofthe successive differences (SDSD) between R-R intervals, etc. Generally,the frequency-domain methods can include calculating a power spectraldensity (PSD) of R-R interval time series data. Calculating the PSD canbe divided into nonparametric, e.g., fast Fourier transform (FFT) basedcalculations and parametric, e.g., autoregressive model, calculations.The PSD can be analyzed by calculating power and peak frequencies fordifferent frequency bands, such as a very low frequency (VLF) band,e.g., in a range of about 0 to 0.04 Hz, a low frequency (LF) band, e.g.,in a range of about 0.04 to 0.15 Hz, and a high frequency (HF) band,e.g., in a range of about 0.15 to 0.4 Hz. The LF band can representsympathetic activity, and the HF band can represent parasympatheticactivity.

In healthy, normal users after meal intake, power in the LF band canincrease, while power in the HF band can decrease. Analysis of LF and HFbands can therefore result in a determination that meal intake hasoccurred when power in the LF band increases a certain threshold amountwhile power in the HF band decreases a threshold amount. Accordingly, inan exemplary embodiment, the computer system 106 can analyze a powerspectral density in LF and HF bands to determine onset of meal intake.Such parameters are described in further detail in Lipsitz et al.,“Hemodynamic And Autonomic Nervous System Responses To Mixed MealIngestion In Healthy Young And Old Subjects And Dysautonomic PatientsWith Postprandial Hypotension,” Circulation, 87: 391-400 (1993) and inLu et al., Digestive Diseases and Sciences, Vol 44 (4) 857-861.

The electrocardiograph output can be received by the computer system 106and can be conditioned and otherwise processed to detect meal intake bythe user. FIG. 6A illustrates an exemplary raw output signal generatedby the electrocardiograph and communicated to the computer system 106.The computer system 106 can analyze the sensor output in segments thatcorrespond to discrete windows of time. For example, the computer system106 can record the sensor output for a predetermined time period (e.g.,10 seconds, 30 seconds, 1 minute, 5 minutes, 10 minutes, etc.) and, atthe conclusion of the predetermined time period or thereafter, analyzethe sensor output corresponding to that time period.

The electrocardiograph output can be processed to identify R waves whichrepresent heart beats. Interbeat intervals NN can then be extracted bythe computer system 106 and various time-domain features can beextracted for a given time period (e.g., 5 minutes). Exemplarytime-domain HRV features include the standard deviation of all NNintervals (SDNN), the square root of the mean of the squares ofdifferences between adjacent NN intervals (RMSSD), and the standarddeviation of differences between adjacent NN intervals (SDSD), each ofwhich can be specified in milliseconds. A spectral analysis can then beperformed using an autoregressive model to obtain variousfrequency-domain features. Exemplary frequency-domain features includethe power in a very low frequency range (less than or equal to 0.04 Hz)(VLF), the power in a low frequency range (0.04 to 0.15 Hz) (LF), andthe power in a high frequency range (0.15-0.4 Hz) (HF). The ratio of LFto HF can also be obtained (LF/HF). Any of these features can be used todetermine whether the meal intake has occurred or is presentlyoccurring.

As shown in FIG. 6B, the SDNN parameter can decrease at the beginning ofmeal intake. Accordingly, SDNN can be used by the computer system 106 tocalculate an index for use in a decision algorithm. For example, thenegative of the moving average filtered value of the first derivative ofthe SDNN can be used. A decrease in SDNN produces a negative slope andthus a negative derivative. These values can be computed for each timesegment, moving average filtered, and negated to be used by a decisionalgorithm in which a feature of interest should increase during mealintake episodes. FIG. 6C illustrates the obtained index, which isexpected to be positive after meal intake episodes.

Time periods with index values below a threshold amount can be excludedas not involving meal intake. Time periods with index values greaterthan or equal to the threshold can be interpreted as meal intake by theuser or, as discussed below, can be used in conjunction with other datato make such an interpretation. In some embodiments, the thresholdamount can be about −3.8. Accordingly, a negative slope based index canbe used by the computer system 106 to determine from theelectrocardiograph output whether digestion is occurring.

Temperature Sensors

The one or more sensors can include a temperature sensor configured tomeasure the user's body temperature. In particular, the user's skintemperature can be measured at one or more locations using temperaturesensors. The temperature sensors can generate an output signal thatrepresents the user's temperature as a function of time. In someembodiments, the temperature sensors can have a sampling rate of about0.2 Hz. Exemplary temperature sensors include the SEN Orange-Sensi MediSystem available from CSEM.

The temperature sensor(s) can be coupled to the user at a variety oflocations. For example, as shown in FIG. 1, temperature sensors 118 canbe coupled to the user's thorax or trunk at a plurality of locations.The temperature sensors can also be coupled to the user's ear lobes. Thetemperature sensor output can be used to determine the user'stemperature and changes in the user's temperature. When a plurality oftemperature sensors are used, a temperature gradient of the user can bemeasured. Thus, in some embodiments, a plurality of temperature sensorscan be coupled to the user's torso to detect the temperature gradientacross the user's torso.

The temperature sensor output can be received by the computer system 106and can be conditioned and otherwise processed to detect ingestion bythe user. For example, increases in user temperature can be associatedwith meal intake. FIG. 7A illustrates exemplary raw output signalsgenerated by upper torso and lower torso temperature sensors andcommunicated to the computer system 106. The illustrated time periodshows the output before, during, and after a meal is consumed by theuser. As shown, the user's skin temperature generally increases duringand after meal ingestion. The computer system 106 can analyze the sensoroutput in segments that correspond to discrete windows of time. Forexample, the computer system 106 can record the sensor output for apredetermined time period (e.g., 10 seconds, 30 seconds, 1 minute, 5minutes, 10 minutes, etc.) and, at the conclusion of the predeterminedtime period or thereafter, analyze the sensor output corresponding tothat time period.

In some embodiments, a positive slope based index can be used toevaluate the temperature sensor output. The computer system 106 cancompute the first derivative of the lower torso skin temperature, asshown in FIG. 7B. A low-pass finite-impulse-response (FIR) filter canthen be applied to the first derivative using a simple moving averagewindow which can be, e.g., 30 minutes in length to extract the lowfrequency components of the first derivative signal, as shown in FIG.7C. The standard deviation of the lower torso skin temperature can thenbe computed and the same FIR filter can be applied to the resultingsignal, as shown in FIG. 7D. The computer system's decision algorithmcan use a temperature index calculated as the ratio of the low frequencycomponents of the first derivative signal to the low frequencycomponents of the standard deviation values. Exemplary index values as afunction of time are shown in FIG. 7E. As shown, the temperature indexcan be positive after meal intake episodes. Time periods with indexvalues below a threshold amount can be excluded as not involving mealintake. Time periods with index values greater than or equal to thethreshold can be interpreted as meal intake by the user or, as discussedbelow, can be used in conjunction with other data to make such aninterpretation. In some embodiments, the threshold amount can be about−0.35. Accordingly, a positive slope based index can be used todetermine from the temperature sensor data whether digestion isoccurring.

Accelerometers

The one or more sensors can include an accelerometer configured to senseor detect movement of one or more portions of the user. Theaccelerometer can generate an output signal that represents the user'smovements as a function of time. In some embodiments, the accelerometercan have a sampling rate of about 30 Hz. Exemplary accelerometersinclude the GT3+ monitor 3D accelerometer available from Actigraph, LLC.

The accelerometer can be coupled to, or configured to measure, movementof various portions of the user. For example, as shown in FIG. 1,3D-axis accelerometers 120 can be embedded into devices worn at thewrist, e.g., such that a first accelerometer is coupled to the user'sleft wrist and a second accelerometer is coupled to the user's rightwrist. In other embodiments, a single accelerometer can be used.Accelerometers can also be coupled to other portions of the user, suchas the user's jaw or throat.

The accelerometer output can be received by the computer system 106 andcan be conditioned and otherwise processed to detect meal intake by theuser. The computer system 106 can analyze the sensor output in segmentsthat correspond to discrete windows of time. For example, the computersystem 106 can record the sensor output for a predetermined time period(e.g., 10 seconds, 30 seconds, 1 minute, 5 minutes, 10 minutes, etc.)and, at the conclusion of the predetermined time period or thereafter,analyze the sensor output corresponding to that time period.

FIG. 8A illustrates an exemplary raw output signal generated by theaccelerometers and communicated to the computer system 106. Theillustrated signals include a time period during which meal ingestionoccurred and, as shown, a discernable pattern of motion occurs duringmeal intake. The 3D information contained in the accelerometer output isshown in FIG. 8B. A principal component analysis (PCA) can be used toproject the 3D-axis components into orthogonal bases with minimalcorrelation, as also shown in FIG. 8B. The PCA components can be used toextract the motion pattern by applying a band-pass FIR filter (e.g.,0.1-0.3 Hz) to the PCA components, as shown in FIG. 8C. The energy ofthese filtered signals can then be computed as shown in FIG. 8D and,from that information, the total energy above a heuristically-definedthreshold (e.g., about 4.0) can be computed to produce an index for thecomputer system's decision algorithm, as shown in FIG. 8E.

Time periods with index values below a threshold index amount can beexcluded as not involving meal intake. Time periods with index valuesgreater than or equal to the threshold can be interpreted as meal intakeby the user or, as discussed below, can be used in conjunction withother data to make such an interpretation. In some embodiments, thethreshold amount can be about 13,767. Accordingly, energy in a frequencyband of interest can be used as an index to determine from theaccelerometer output when meal intake activities are occurring.

Electrogastrographs (EGG)

The one or more sensors can include an electrogastrograph (“EGG”) or anelectrogastroenterograph configured to sense or detect electricalactivity of the user's gastrointestinal system (e.g., stomach, smallintestine, colon, and so forth). The electrogastrograph can generate anoutput signal that represents electrical activity as a function of time.The electrogastrograph can include surface leads or electrodesconfigured for attachment to the user's skin and/or implantable leads orelectrodes configured to be placed within the user. In some embodiments,the electrogastrograph can have a sampling rate of about 312.5 Hz.Exemplary electrogastrographs include the Biopac MP150 Data AcquisitionSystem and the Biopac EGG100C available from Biopac Systems, Inc.

The electrogastrograph electrodes can be coupled to, or configured tomeasure, various portions of the user. For example, as shown in FIG. 1,the electrogastrograph electrodes 122 can be coupled to various placeson the user's abdomen.

The electrogastrograph output can be received by the computer system 106and can be conditioned and otherwise processed to detect meal intake bythe user. The computer system 106 can analyze the sensor output insegments that correspond to discrete windows of time. For example, thecomputer system 106 can record the sensor output for a predeterminedtime period (e.g., 10 seconds, 30 seconds, 1 minute, 5 minutes, 10minutes, etc.) and, at the conclusion of the predetermined time periodor thereafter, analyze the sensor output corresponding to that timeperiod.

FIG. 9A illustrates an exemplary raw output signal generated by theelectrogastrograph and communicated to the computer system 106. In someembodiments, the local energy of the electrogastrograph output filteredin a frequency zone of interest can be used as an index for the computersystem's decision algorithm. The computer system 106 can filter the EGGoutput in the frequency domain of the intestine (e.g., 0.01-0.03 Hz), asshown in FIG. 9B. A saturation can be applied on the filtered signal toreduce motion-induced artifacts, as shown in FIG. 9C. The sliding energyof the cropped-filtered signals can then be computed and the totalenergy can be used as an index.

Time periods with index values below a threshold amount can be excludedas not involving meal intake. Time periods with index values greaterthan or equal to the threshold can be interpreted as meal intake by theuser or, as discussed below, can be used in conjunction with other datato make such an interpretation. In some embodiments, the thresholdamount can be about 0.015. Accordingly, an amplitude-based index can beused to determine from the electrogastrograph output whether digestionis occurring.

Impedance Sensors

The one or more sensors can include an impedance sensor configured tosense or measure the impedance across one or more portions of the user'sbody. The impedance sensor can generate an output signal that representsthe impedance as a function of time. The impedance sensor can includesurface leads or electrodes configured for attachment to the user's skinand/or implantable leads or electrodes configured to be placed withinthe observed portion of the user, e.g., in the form of needles or wires.In some embodiments, the impedance sensor can have a sampling rate ofabout 312.5 Hz. Exemplary impedance sensors include the Biopac MP150Data Acquisition System and the Biopac EBI100C available from BiopacSystems, Inc.

The impedance sensor electrodes can be coupled to, or configured tomeasure, various portions of the user. For example, as shown in FIG. 1,the impedance sensor electrodes 124 can be coupled to the user's neck.Each time a bolus of ingested solids or liquids passes through theuser's neck, a change in impedance can be observed. As shown in FIG.10A, respiration and chewing artifacts can also be observed in theimpedance sensor output.

The impedance sensor output can be received by the computer system 106and can be conditioned and otherwise processed to detect meal intake bythe user. The computer system 106 can analyze the sensor output insegments that correspond to discrete windows of time. For example, thecomputer system 106 can record the sensor output for a predeterminedtime period (e.g., 10 seconds, 30 seconds, 1 minute, 5 minutes, 10minutes, etc.) and, at the conclusion of the predetermined time periodor thereafter, analyze the sensor output corresponding to that timeperiod.

FIG. 10A illustrates an exemplary raw output signal generated by theimpedance sensor, with inset portions showing the output during chewingand during respiration. The output signal can be communicated to thecomputer system 106, which can use an energy-based index to determinewhen ingestion is occurring. The computer system 106 can apply aband-pass FIR filter on the impedance-measurement signals. The chewingband can be fixed between, e.g., 1.5 to 2.5 Hz. The median energy in thefrequency range of interest can be used as an index for the computersystem's decision algorithm. The estimated energy as a function of timeis shown in FIG. 10B, in which meal intake began at T=360 s. As shown,estimated energy peaks coincide with meal intake.

Time periods with index values below a threshold amount can be excludedas not involving meal intake. Time periods with index values greaterthan or equal to the threshold can be interpreted as meal intake by theuser or, as discussed below, can be used in conjunction with other datato make such an interpretation. In some embodiments, the thresholdamount can be about 1.4×10⁻⁵. Accordingly, an energy-based index can beused to determine from the impedance sensor output when chewing occurs.

Impedance of other portions of the user's body can also be sensedincluding, for example, the impedance across the user's stomach wall.Sensing and processing gastric impedance data and/or using changes ingastric impedance to detect eating is described in more detail in U.S.Pat. Pub. No. 2009/0192404 filed Jan. 28, 2008 entitled “Methods AndDevices For Measuring Impedance In A Gastric Restriction System,” Silnyet al, “Verification of the intraluminal multiple electrical impedancemeasurement for the recording of gastrointestinal motility,”Neurogastroenterology & Motility, Vol 5(2): 107-122 (June 1993); and“Effects of Thickened Feeding on Gastroesophageal Reflux in Infants: APlacebo-Controlled Crossover Study Using Intraluminal Impedance,”Pediatrics 111(4), e355-e359 (April 2003).

FIGS. 11A-11F illustrate various exemplary patterns in which theimpedance sensor electrodes can be coupled to the user.

In FIG. 11A, the I− and I+ electrodes are coupled to opposite sides ofthe user's throat, just beneath the jaw. The V− and V+ electrodes arecoupled to opposite sides of the user's neck, at the base of the neck,just above the clavicle and in front of the trapezius.

In FIG. 11B, the I− and I+ electrodes are coupled to the user's rightand left trapezius muscles, respectively, about half way between theuser's neck and shoulder. The V− and V+ electrodes are coupled toopposite sides of the user's chest, just below the clavicle and abouthalf way between the user's neck and shoulder.

In FIG. 11C, the I− and I+ electrodes are coupled to opposite sides ofthe user's chest, just below the clavicle and about half way between theuser's neck and shoulder. The V− and V+electrodes are coupled toopposite sides of the user's chest, just beneath the I− and I+electrodes and inward towards the sternum.

In FIG. 11D, the I− and I+ electrodes are coupled to the user's rightand left trapezius muscles, respectively, about half way between theuser's neck and shoulder. The V− and V+ electrodes are coupled toopposite sides of the user's chest, beneath the clavicle and closer tothe sternum than to the shoulder.

In FIG. 11E, the I− and I+ electrodes are coupled to opposite sides ofthe user's back, just below the base of the neck. The V− and V+electrodes are coupled to opposite sides of the user's chest, just belowthe clavicle and about half way between the user's neck and shoulder.

In FIG. 11F, the I− and I+ electrodes are coupled to opposite sides ofthe user's back, just below the base of the neck. The V− and V+electrodes are coupled to the user's right and left trapezius muscles,respectively, about half way between the user's neck and shoulder.

The output graphs that accompany each electrode placement diagramillustrate exemplary impedance power spectral density (PSD) as detectedby the impedance sensor during chewing and non-chewing episodes. Asshown, the electrode placement of FIGS. 11A-11C can provide a PSD ofabout 0.05 at 1.5 Hz during chewing episodes, which can be readilydistinguished from non-chewing episodes. The electrode placement ofFIGS. 11D-11F can result in less of a distinction in the sensor outputbetween chewing and non-chewing episodes. While the electrode placementof FIG. 11A can provide the strongest response to chewing episodes, theelectrode placement of FIGS. 11B-11C can be preferred in someembodiments, as these placements can be easily hidden under the user'sclothing and also provide a strong response to chewing episodes. It willbe appreciated that a variety of other electrode placements can be usedin addition to those specifically illustrated and described herein.

Heart Rate Sensors

While ECG sensors are disclosed above for detecting the user's heartrate, it will be appreciated that other heart rate sensors can be usedinstead or in addition. Heart rate sensors can be configured to gatherheart rate data for the user, including changes in heart rate, e.g.,HRV. Heart rate sensors can be subcutaneously positioned or implantedwithin the user, e.g., at the distal esophagus, the proximal stomach, orthe mid/distal stomach. Heart rate sensors can also be transcutaneouslypositioned or positioned external to the user such as positioned on anexternal skin surface thereof. One or more heart rate sensors can bedisposed at a variety of locations around the user, e.g., the wrist andthe sternum, and each of the heart rate sensors can be configured tocommunicate sensed data to the computer system 106.

Externally-located heart rate sensors can include a strap configured tobe worn by the user such that a heart rate sensing electrode attached tothe strap is positioned on an exterior skin surface of a chest of theuser, a heart rate sensing electrode attached to an article of clothingconfigured to be worn by the user such that the electrode contacts anexterior skin surface of the user, and a pulse oximeter configured to bepositioned on an external skin surface of a finger of a user. Exemplaryembodiments of a heart rate sensor configured to be positioned withinthe user include a lead configured to be implanted within a heart of theuser, and an electrode configured to be implanted on a thorax of theuser.

pH Sensors

The one or more sensors can include a pH sensor configured to gatherdigestive tract pH levels of the user, e.g., pH levels within the user'sstomach. A pH sensor can be implanted in the user, such as within agastrointestinal tract of the user, e.g., within the user's stomach,within the user's intestine, within the user's mouth (e.g., a dentalimplant), etc.

Variations in gastric pH can indicate whether or not there is solid foodpresent in the stomach. The relationship between gastric pH levels andfood consumption is described in further detail in “RegionalPostprandial Differences in pH Within the Stomach and GastroesophagealJunction,” Digestive Diseases and Sciences, Vol. 50, No. 12 (December2005), pgs. 2276-2285. Using intraluminal pH sensors to detect eating isdescribed in more detail in “Effects of Thickened Feeding onGastroesophageal Reflux in Infants: A Placebo-Controlled Crossover StudyUsing Intraluminal Impedance,” Pediatrics 111(4), e355-e359 (April2003). In general, gastric pH is low in an empty stomach. Upon eating,especially foods that contain protein, gastric pH can become more basic(i.e., the pH value increases) due to buffering by the food. Theincrease in pH can occur even though the stomach is actively secretingacid. Once the buffering capacity of the food is exceeded, the gastricpH can return to a low value. Thus, as described in further detail inU.S. Pat. Pub. No. 2009/0192534 filed Jan. 29, 2008 entitled “SensorTrigger” and in “Regional Postprandial Differences in pH Within theStomach and Gastroesophageal Junction,” Diseases and Sciences, Vol. 50,No. 12 (December 2005), the gastric pH level can increase after eachmeal and return to the baseline pH sometime thereafter.

The pH sensor can be configured to communicate the sensed data to thecomputer system 106. The computer system 106 can in turn be configuredto determine whether a change in gastric pH of a selected magnitudeoccurred, e.g., |X-Y| pH, or whether the pH rises above a thresholdvalue, e.g., above about 7. Time periods in which the pH exceeds thethreshold or in which pH changes of a selected magnitude occur can beinterpreted as meal intake by the user or, as discussed below, can beused in conjunction with other data to make such an interpretation.Accordingly, gastric pH sensors can be used to determine when digestionoccurs.

Gastric Stretch Sensors

In some embodiments, the one or more sensors can include a gastricstretch sensor, e.g., a strain gauge and strap disposed around theuser's abdomen. Various embodiments of collecting and/or analyzinggastric stretch data to determine when eating occurs are described inmore detail in Paintal, et al., “A Study Of Gastric Stretch Receptors:Their Role In The Peripheral Mechanisms Of Satiation Of Hunger AndThirst,” Journal of Physiology, Vol. 126, 255-270 (1954), and Geliebteret al., “Gastric Distension By Balloon And Test-Meal Intake In Obese AndLean Subjects,” Am J Clin Nutr, Vol 48, 592-594 (1988).

Combinations of Sensors

As noted above, the computer system 106 can be configured to make a mealintake determination based on the output of a single sensor or based onthe output of a plurality of sensors. A number of exemplary sensorcombinations are discussed below, however it will be appreciated thatvirtually any combination of the sensors described herein can be used.

As shown in FIG. 12, the EMG and impedance sensors can have highsensitivity and high specificity when distinguishing between solid foodintake and other activities such as drinking, resting, and exercising.The accelerometer and microphone sensors can have high sensitivity andhigh selectivity when distinguishing between solid or liquid food intakeand other activities such as resting and exercising. The temperature,HRV, and EGG sensors can have relatively lower sensitivity and/orspecificity when determining when digestion is occurring.

In some embodiments, the one or more sensors can include an EMG sensorand an accelerometer, and can be effective to detect solid and liquidfood intake with high specificity and high sensitivity. For example, thecomputer system 106 can be configured to detect that solid food intakeoccurs when the EMG sensor exceeds the index threshold. The computersystem 106 can be configured to detect that drinking occurs when the EMGsensor is below the index threshold and the accelerometer is above theindex threshold. When neither sensor is above the index threshold, thecomputer system 106 can determine that no solid food intake or drinkingis occurring.

In some embodiments, the one or more sensors can include an impedancesensor and an accelerometer, and can be effective to detect solid andliquid food intake with high specificity and high sensitivity. Forexample, the computer system 106 can be configured to detect that solidfood intake occurs when the impedance sensor exceeds the indexthreshold. The computer system 106 can be configured to detect thatdrinking occurs when the impedance sensor is below the index thresholdand the accelerometer is above the index threshold. When neither sensoris above the index threshold, the computer system 106 can determine thatno solid food intake or drinking is occurring.

In some embodiments, the one or more sensors can include an EMG sensorand a microphone, and can be effective to detect solid and liquid foodintake with high specificity and high sensitivity. For example, thecomputer system 106 can be configured to detect that solid food intakeoccurs when the EMG sensor exceeds the index threshold. The computersystem 106 can be configured to detect that drinking occurs when the EMGsensor is below the index threshold and the microphone is above theindex threshold. When neither sensor is above the index threshold, thecomputer system 106 can determine that no solid food intake or drinkingis occurring.

In some embodiments, the one or more sensors can include an impedancesensor and a microphone, and can be effective to detect solid and liquidfood intake with high specificity and high sensitivity. For example, thecomputer system 106 can be configured to detect that solid food intakeoccurs when the impedance sensor exceeds the index threshold and themicrophone exceeds the index threshold. The computer system 106 can beconfigured to detect that drinking occurs when the impedance sensor isbelow the index threshold and the microphone is above the indexthreshold. When neither sensor is above the index threshold, thecomputer system 106 can determine that no solid food intake or drinkingis occurring.

As shown in FIG. 13, sensor combinations can advantageously allow solidfood intake and drinking to be distinguished from other activities suchas resting and exercising with high sensitivity and specificity.

Controlled Devices

As noted above, a controlled device 108 can be coupled to the mealdetection system 100 such that the meal detection system is configuredto trigger, modulate, or otherwise control the controlled device 108based on determinations made by the computer system 106. In particular,when the computer system 106 determines that meal intake has occurred oris presently occurring, it can trigger, modulate, or otherwise controlone or more controlled devices 108.

The computer system 106 can be configured to transmit a trigger signalto the controlled device 108. The trigger signal can have a variety ofconfigurations, such as a simple on/off signal configured to change thecontrolled device 108 from a dormant or off mode, in which thecontrolled device 108 does not deliver therapy or record that mealintake has occurred, to a delivery or on mode in which the controlleddevice 108 delivers a therapy to the user or records that meal intakehas occurred. The trigger signal can trigger a timer at the controlleddevice 108 that can initiate delivery of a therapy after a predeterminedperiod of time has passed, e.g., 15 minutes, etc., such that the therapycan be initiated a certain amount of time after the detection of a mealhas occurred. The trigger signal can optionally include data related tothe meal ingested by the user, e.g., an amount or estimated amount offood eaten. The controlled device 108 can be configured to record thisdata for subsequent analysis or reporting. Alternatively or in addition,the controlled device 108 can be configured to use such data todetermine an amount of therapy to deliver to the user, e.g., a certainvolume of chemical to be delivered thereto, and/or a length of time todeliver the therapy to the user. The computer system 106 can beconfigured to include with the trigger signal instructions regarding theamount of the therapy to deliver to the user and/or the length of timeto deliver the therapy to the user. In some embodiments, aftertransmitting the trigger signal to the controlled device 108, thecomputer system 106 can be configured to transmit a second, subsequenttrigger signal to the controlled device 108 to cause the device to stopdelivering the therapy to the user. The second, subsequent triggersignal can be sent for any number of reasons, such as after a certainperiod of time or if, based on sensed data gathered by the at least onesensor 104, the computer system 106 determines that the user has ceasedmeal intake.

Upon receipt of the trigger signal, the controlled device 108 can beconfigured to deliver a therapy to the user for any length of time. Insome embodiments, the trigger signal can be configured to triggerdelivery of the therapy for an indefinite period of time. In otherwords, the controlled device 108 can be configured to have a default offmode in which the device does not deliver the therapy to the user, andbe configured to permanently switch to an on mode during which thedevice 108 delivers the therapy to the user. The indefinite period oftime can be established by an amount of the therapy available to thedevice 108, e.g., if the device 108 includes a finite supply of achemical therapy, can be defined by an amount of power available to thedevice 108, e.g., battery life, and/or can be defined by alikely-unknown period of time before a predetermined termination eventoccurs that triggers an end of the therapy's delivery to the user. Thepredetermined termination event can include, e.g., an end of a mealintake episode as determined by the computer system 106 and communicatedfrom the computer system to the controlled device 108. In otherembodiments, the trigger signal can be configured to trigger delivery ofthe therapy for a predetermined time period, e.g., a period of “N”seconds, minutes, etc. in which the device 108 is configured to deliverthe therapy to the user before stopping delivery thereof if and untilthe computer system 106 communicates another trigger signal to thedevice 108 to again start delivery of the therapy.

The device 108 can therefore be configured to intermittently deliver thetherapy to the user. In other words, the device can be configured tohave a default off mode in which the device does not deliver therapy tothe user, and be configured to change from the off mode to an on modefor the predetermined time period during which the device delivers thetherapy to the user before returning to the off mode. Further,triggering delivery of the therapy at generally unpredictable intervals,e.g., whenever the user ingests a meal, can help prevent the user's bodyfrom adapting to a particular therapy by learning to expect the therapyat certain times.

The controlled device 108 can be defaulted to a dormant mode untiltriggered by detected meal intake. Various exemplary embodiments ofdevices having a dormant mode, as well as various exemplary embodimentsof powering a system including a sensor and of transmitting signals, aredescribed in further detail in U.S. Pat. Pub. No. 2010/0056948 filedAug. 25, 2009 entitled “Stimulation Of Satiety Hormone Release” and U.S.Pat. Pub. No. 2009/0192404 filed Jan. 28, 2008 entitled “Methods AndDevices For Measuring Impedance In A Gastric Restriction System.”Exemplary controlled devices are disclosed in U.S. Pat. Pub. No.2012/0172792 filed Dec. 29, 2010 entitled “Obesity Therapy And HeartRate Variability.”

Electrical Stimulation

In some embodiments, the controlled device 108 can be configured todeliver electrical stimulation to the user's tissue, e.g., a stomachwall of the user, an intestinal wall of the user, individual nerves ornerve bundles innervating a target tissue of interest, etc., e.g., forthe treatment of obesity and/or co-morbidities.

Because the controlled device 108 can be configured to intermittentlydeliver stimulation therapy to the user only when triggered by detectedmeal intake, nerve and/or tissue desensitization to electrical signalsand nerve and/or tissue damage can be reduced, if not entirelyprevented, because the electrical signal is not continuously deliveredto the nerve and/or tissue. Moreover, when triggered to begin deliveryof the stimulation therapy by the computer system 106, the controlleddevice 108 can be configured to non-continuously deliver the electricalsignal to the user such that the signal is alternately “off” and “on”when the controlled device 108 is in the on mode. The periods of time inwhich the signal is “off” and “on” can be the same or different from oneanother. In exemplary embodiments, the signal can be “off” for a longerperiod of time than it is “on,” which can help reduce, if not prevent,nerve and/or tissue desensitization to electrical signals and nerveand/or tissue damage. Delivering an electrical signal that is “off” fora longer period of time than it is “on” can also help conserve power,e.g., reduce battery consumption, and can reduce the size of a powersupply required to power the controlled device 108. However, thecontrolled device 108 can be configured to continuously deliver theelectrical signal to the user, e.g., continuously delivered indefinitelyor continuously delivered during a predetermined time period of “N”minutes after the computer system 106 triggers the controlled device108.

The electrical signal can be applied to more than one location ontissue, e.g., gastrointestinal tissue, of the user. For example, theelectrical signal can be applied to two, three, four, or more locationsin a distal ileum of the user. A “location” can be defined by the areaof physical contact between the tissue and a means for delivery of theelectrical stimulus, e.g., a first electrode of the controlled device108. Accordingly, the application of the electrical signal to a secondlocation on the tissue of the user can include contacting a secondelectrode of the controlled device 108 with a portion of the tissue thatis not in physical contact with the first electrode also electricallystimulating the user.

The electrical signal can have a variety of configurations. Exemplaryelectrical parameters of the electrical signal that can be variedinclude frequency, voltage, current, and pulse duration. The electricalsignal can have a frequency of about 0.1 Hz to about 90 Hz; for example,the electrical signal can have a frequency of about 0.1 Hz, about 0.15Hz, about 0.2 Hz, about 0.4 Hz, about 1 Hz, about 4 Hz, about 10 Hz,about 20 Hz, about 25 Hz, about 30 Hz, about 35 Hz, about 40 Hz, about50 Hz, about 70 Hz, or about 90 Hz. The electrical signal can have avoltage of about 0.5 V to about 25 V; for example, the voltage can beabout 1 V, about 2 V, about 5 V, about 10 V, about 14V; about 15 V,about 20 V, or about 25 V. The electrical signal can have a currentbetween about 2 mA and about 10 mA. The electrical signal can have apulse duration of about 3 ms to about 500 ms; for example, the pulseduration may be about 5 ms, about 50 ms, about 100 ms, about 150 ms,about 200 ms, about 250 ms, about 300 ms, about 350 ms, about 400 ms,about 450 ms, or about 500 ms. In some embodiments, the electricalsignal can be applied at a voltage of about 14V, with a pulse durationof about 5 ms, and at a stimulus frequency of about 20 to about 80 Hz;with respect to such embodiments, the stimulus frequency can be, forexample, about 20 Hz, about 40 Hz, or about 80 Hz. In other embodiments,the electrical signal can be applied at a voltage of about 14 V, with apulse duration of about 300 ms, and at a frequency of about 0.4 Hz.Various exemplary embodiments of an electrical signal that can bedelivered to a user are described in more detail in U.S. Pat. Pub. No.2010/0056948 filed Aug. 25, 2009 entitled “Stimulation Of SatietyHormone Release.”

An electrical signal can be delivered to the user in any number of waysto electrically stimulate the user. FIG. 14 illustrates an exemplaryembodiment of a controlled device 1100 configured to generate anddeliver an electrical signal to a user. Although the illustratedcontrolled device 1100 is implantable, a controlled device configured todeliver electrical stimulation to a user can be subcutaneously ortranscutaneously positioned, as mentioned above. The controlled device1100 can include a housing 1102 coupled to a suitable power source orbattery 1104, such as a lithium battery, a first waveform generator1106, and a second waveform generator 1108. As in the illustratedembodiment, the battery 1104 and first and second waveform generatorscan be located within the housing 1102. In other embodiments, a batterycan be external to a housing and be wired or wirelessly coupled thereto.The housing 1102 is preferably made of a biocompatible material. Thefirst and second waveform generators 1106, 1108 can be electricallycoupled to and powered by the battery 1104. The waveform generators1106, 1108 can be of any suitable type, such as those sold by TexasInstruments of Dallas, Tex. under model number NE555. The first waveformgenerator 1106 can be configured to generate a first waveform or lowfrequency modulating signal 1108, and the second waveform generator 1110can be configured to generate a second waveform or carrier signal 1112having a higher frequency than the first waveform 1108. Low frequencymodulating signals cannot, in and of themselves, pass through bodytissue to effectively stimulate target nerves. The second waveform 1108can, however, to overcome this problem and penetrate through bodytissue. The second waveform 1112 can be applied along with the firstwaveform 1108 to an amplitude modulator 1114, such as the modulatorhaving the designation On-Semi MC1496, which is sold by TexasInstruments.

The modulator 1114 can be configured to generate a modulated waveform1116 that is transmitted through a lead 1118 to one or more electrodes1120. Four electrodes are illustrated, but the device 1100 can includeany number of electrodes having any size and shape. The lead 1118 can beflexible, as in the illustrated embodiment. The electrodes 1120 can beconfigured to, in turn, apply the modulated waveform 1116 to a targettissue or nerve 1122 to stimulate the target 1122. The first and secondwaveforms 1108, 1112 can have any shape, e.g., the first waveform 1108can be a square wave, and the second waveform 1112 can be a sinusoidalsignal. Although an electrical signal is described that includes carrierand modulating signals, an electrical signal delivered to a user canalternatively include only one of a carrier and modulating signal.

Various exemplary embodiments of methods and devices for delivering anelectrical signal to a user are described in more detail in U.S. Pat.Pub. No. 2011/0270360, filed on Dec. 29, 2010 entitled “Methods AndDevices For Activating Brown Adipose Tissue,” U.S. Pat. Pub. No.2009/0132018 filed Nov. 16, 2007 entitled “Nerve Stimulation Patches AndMethods For Stimulating Selected Nerves,” U.S. Pat. Pub. No.2010/0056948 filed Aug. 25, 2009 entitled “Stimulation Of SatietyHormone Release,” U.S. Pat. Pub. No. 2008/0147146 filed Dec. 19, 2006entitled “Electrode Patch And Method For Neurostimulation,” U.S. Pat.Pub. No. 2005/0277998 filed Jun. 7, 2005 entitled “System And Method ForNerve Stimulation,” U.S. Pat. Pub. No. 2006/0195153 filed Jan. 31, 2006entitled “System And Method For Selectively Stimulating Different BodyParts,” U.S. Pat. Pub. No. 2007/0185541 filed Aug. 2, 2006 entitled“Conductive Mesh For Neurostimulation,” U.S. Pat. Pub. No. 2006/0195146filed Jan. 31, 2006 entitled “System And Method For SelectivelyStimulating Different Body Parts,” U.S. Pat. Pub. No. 2008/0132962 filedDec. 1, 2006 entitled “System And Method For Affecting GastricFunctions,” U.S. Pat. Pub. No. 2008/0147146 filed Dec. 19, 2006 entitled“Electrode Patch And Method For Neurostimulation,” U.S. Pat. Pub. No.2009/0157149 filed Dec. 14, 2007 entitled “Dermatome Stimulation DevicesAnd Methods,” U.S. Pat. Pub. No. 2009/0149918 filed Dec. 6, 2007entitled “Implantable Antenna,” U.S. Pat. Pub. No. 2009/0132018 filedNov. 16, 2007 entitled “Nerve Stimulation Patches And Methods ForStimulating Selected Nerves,” U.S. Pat. Pub. No. 2010/0161001 filed Dec.19, 2008 entitled “Optimizing The Stimulus Current In A Surface BasedStimulation Device,” U.S. Pat. Pub. No. 2010/0161005 filed Dec. 19, 2008entitled “Optimizing Stimulation Therapy Of An External StimulatingDevice Based On Firing Of Action Potential In Target Nerve,” U.S. Pat.Pub. No. 2010/0239648 filed Mar. 20, 2009 and entitled “Self-Locating,Multiple Application, And Multiple Location Medical Patch Systems AndMethods Therefor,” and U.S. Pat. Pub. No. 2011/0094773 filed Oct. 26,2009 entitled “Offset Electrodes.”

Various exemplary embodiments of devices configured to directly apply anelectrical signal to stimulate nerves are described in more detail inU.S. Pat. Pub. No. 2005/0177067 filed Jan. 26, 2005 entitled “System AndMethod For Urodynamic Evaluation Utilizing Micro-Electronic MechanicalSystem,” U.S. Pat. Pub. No. 2008/0139875 filed Dec. 7, 2006 entitled“System And Method For Urodynamic Evaluation Utilizing MicroElectro-Mechanical System Technology,” U.S. Pat. Pub. No. 2009/0093858filed Oct. 3, 2007 entitled “Implantable Pulse Generators And MethodsFor Selective Nerve Stimulation,” U.S. Pat. Pub. No. 2010/0249677 filedMar. 26, 2010 entitled “Piezoelectric Stimulation Device,” U.S. Pat.Pub. No. 2005/0288740 filed Jun. 24, 2004 entitled, “Low FrequencyTranscutaneous Telemetry To Implanted Medical Device,” U.S. Pat. No.7,599,743 filed Jun. 24, 2004 entitled “Low Frequency TranscutaneousEnergy Transfer To Implanted Medical Device,” U.S. Pat. No. 7,599,744filed Jun. 24, 2004 entitled “Transcutaneous Energy Transfer PrimaryCoil With A High Aspect Ferrite Core,” U.S. Pat. No. 7,191,007 filedJun. 24, 2004 entitled “Spatially Decoupled Twin Secondary Coils ForOptimizing Transcutaneous Energy Transfer (TET) Power TransferCharacteristics,” and European Pat. Pub. No. 377695 published as Int'l.Pat. Pub. No. WO1989011701 published Nov. 30, 2004 and entitled“Interrogation And Remote Control Device.”

Drug Delivery

The controlled device 108 can be configured to administer a therapeuticagent, e.g., a natural or an artificial chemical, solution, activeingredient, nutrient, drug, medicant, nutraceutical, or pharmaceuticalto a user.

The therapeutic agent can be delivered to the user in any number ofways. FIG. 15 illustrates one exemplary embodiment of a controlleddevice 108 in the form of a delivery device 212, e.g., an active agentcatheter delivery system, configured to deliver a therapeutic agent to auser. The delivery device 212 is shown implanted within an intestine ofa user, but the delivery device 212 can be implanted in a variety oflocations and can be implanted in a variety of ways, e.g., implantedlaparaoscopically, deployed within the colon through a natural orificeprocedure, etc. Various exemplary embodiments, including the deliverydevice 212, of methods and devices for delivering a therapeutic agent toa user are described in more detail in U.S. Pat. Pub. No. 2005/0038415filed Jul. 12, 2004 entitled “Method And Apparatus For Treatment OfObesity.”

Generally, the delivery device 212 can include an active agent reservoirand pump 210 and an active agent delivery catheter 220. Although anyactive agent reservoir and pump and active agent delivery catheter canbe used, an exemplary embodiment of an active agent reservoir and pumpincludes a MEDSTREAM™ Programmable Infusion Pump, available from Codman& Shurtleff, Inc. of Raynham, Mass., and an exemplary embodiment of anactive agent delivery catheter includes a Codman® silicone taperedarterial catheter, available from Codman & Shurtleff, Inc. The reservoirand pump 210 can include any suitable reservoir and/or fluid deliverypump, e.g., having, as shown in FIG. 16, a resealable fluid insertionboss 213, a fluid reservoir 211, a fluid pump 214, and a radiallyextended male fluid delivery port 215.

In use, a therapeutic agent contained in the reservoir 211 can bedispensed therefrom, through the catheter 220, (e.g., into the ileum ofthe user in order to decrease intestinal motility and increase feelingsof satiety experienced by the user). Optionally, the reservoir 211 canbe recharged at any time necessary. Preferably, recharging of thereservoir 211 is performed without removal from the implantation sitebut is performed transcutaneously such as, for example, by injectionwith a syringe. The active agent delivery catheter 220, as shown in FIG.17, can include a female port 221 positioned at a first terminal end ofcatheter 220 and configured to mate with the male fluid delivery port215 of the reservoir and pump 210. The catheter 220 can include anelongate fluid transmission lumen 222 extending from the female port 221to a second terminal end of the catheter 220. Positioned near the secondterminal end of the catheter 220 and around a circumference of the lumen222 can be a first laterally extending brace 223. A second laterallyextending brace 224 can positioned distally to the first laterallyextending brace 223 in close proximity to the second terminal end of thecatheter 220. The catheter 220 can also include a balloon 225 configuredto secure the catheter 220 within, e.g., the user's abdominal cavity,wherein a securing means, such as a row of purse-string sutures, can beplaced and tightened around an opening in the intestine to secure theintestine to the catheter 220. The balloon 225 can then be pulled tautagainst the sealing means to prevent leakage of intestinal contents.

Ileal Brake Nutrients

The controlled device 108 can be configured to administer any substance(e.g., a nutrient) configured to provoke a release of one or morehormones from L-cells, such as linoleic acid (LA), a carbohydrate, othersugars, an amino acid, a protein, a fatty acid, a fat, or anycombination thereof. The nutrient can take the form of a natural fooditem; a supplement, e.g., a nutrition drink; or a substance that is madewith the express purpose of stimulating L-cells, and therefore need notbe a “nutrient” per se in the conventional sense. Generally, delivery ofthe nutrient to the user, such as to the user's intestine, e.g., anileum of the intestine, can help trigger ileal brake. Normally, thepresence of nutrients, which arise from a meal consisting ofcarbohydrates, fats and proteins, termed “digesta” in the digestivetract, stimulates release of the body's own incretins into the bloodstream. Key hormones, released by specialized L-cells located in themucosa, which is the innermost interior (luminal) wall of theintestines, coordinate the body's response to a meal. The hormonesproduce this effect by inducing a sense of fullness and cessation ofeating (satiety), triggering the release of insulin to maintain properglucose levels (incretin effect) and slowing the passage of contentsthrough the digestive tract (delaying gastric emptying and slowing smallintestinal transit). Collectively, these effects have been termed theileal brake. By delivering the nutrient, e.g., triggering ileal brake,at the onset of the user ingesting a meal, satiation can occur earlierthan it would in a normal digestive process without the delivery of thenutrient to the user. The user can therefore feel full faster afterbeginning to eat, thereby encouraging smaller amounts of food intakeand, over time, encouraging weight loss. Triggering ileal brake andvarious exemplary embodiments of nutrients and administration thereof toa user to help treat obesity are described in more detail in U.S. Pat.Pub. No. 2010/0056948 filed Aug. 25, 2009 entitled “Stimulation OfSatiety Hormone Release.”

Insulin

The controlled device 108 can be an insulin pump, continuous glucosemeter, or artificial pancreas. Meal detection using the meal detectionsystem 100 described herein can be used with the insulin pump orartificial pancreas to control insulin release, instead of or inaddition to the continuous blood glucose sensors that are typicallyused. The system 100 can allow for earlier triggering than relyingsolely on measurement of interstitial glucose. The system 100 can alsoallow for less frequent blood glucose sampling, allowing for a moredormant duty cycle to increase battery life. The system 100 can detectwhen exercise is occurring (e.g., by detecting sustained elevated heartrate or repeated body movements consistent with running or exercising),which can be considered in determining the timing and quantity ofinsulin delivery. The system 100 can also allow for meal size or mealduration to be estimated, and can be used to maintain a log of mealintake for user education, accountability, or awareness. Exemplaryinsulin pumps and/or artificial pancreases are disclosed in U.S. Pat.No. 4,515,584 issued on May 7, 1985 entitled “Artificial Pancreas”; U.S.Pat. No. 6,023,009 issued on Feb. 8, 2000 entitled “ArtificialPancreas”; and U.S. Pat. No. 8,346,399 issued on Jan. 1, 2013 entitled“Programmable Insulin Pump.” It will be appreciated that any of thedevices or methods disclosed in the foregoing references can be modifiedin accordance with the teachings herein to trigger insulin release inresponse to meal intake detected by the computer system 106.

Bile Acid Modulation

The controlled device 108 can be configured to deliver a compositioneffective to modulate bile acid levels in the user, e.g., to treat ametabolic disorder. Exemplary methods and devices for modulating bileacid are disclosed in U.S. application Ser. No. 13/631,095, filed onSep. 28, 2012 and entitled “Methods and Compositions of Bile Acids.” Itwill be appreciated that any of the devices or methods disclosed in theforegoing reference can be modified in accordance with the teachingsherein to modulate bile acid levels based on meal intake detected by thecomputer system 106.

pH Therapy

The controlled device 108 can be configured to deliver a composition,e.g., bicarbonate, effective to modulate pH in the user's stomach or inother portions of the user's digestive tract. For example, the device108 can be configured to release a composition to increase gastric pHduring meal intake when said intake is detected by the computer system106. Increasing the pH can prevent certain digestive enzymes responsiblefor breaking down proteins, such as pepsin, from being activated. Insome embodiments, the device 108 can modulate gastric pH during mealintake to a level of at least about 2.4, at least about 3, at leastabout 5, and/or at least about 7.

Other Drugs

The controlled device 108 can be configured to deliver other drugs,including GLP-1 agonists (e.g., exenatide (“Byetta”) or liraglutide(“Victoza”)), activators of Brown Adipose Tissue (e.g., norepinephrine,etc.), Melanocortin Four Receptor Agonists, and other agents that impactmetabolic function.

Aversive Response

The controlled device 108 can be configured to cause or provoke anaversive response in the user when the user exceeds a certain thresholdof meal intake (e.g., to discourage the user from overeating). Thethreshold can be defined by meal onset, meal volume, meal content (typeof food), intake rate, meal duration, and/or meal conclusion. Theaversive therapy can be mechanical, electrical, and/or chemical innature. Exemplary aversive responses include satiety, upset stomach,vomiting, diarrhea, abdominal cramps, nausea, and audible or visual usernotifications. For example, the controlled device 108 can be configuredto deliver lithium chloride to the user when the computer system 106detects that the meal volume or meal duration has exceeded a threshold.The meal volume or duration threshold can be based on a variety offactors, including a normal or prescribed caloric intake for the user.Exemplary devices and methods for creating aversive responses in theform of satiety, upset stomach, vomiting, abdominal cramps, nausea, andaudible or visual user notifications are disclosed in InternationalPublication No. WO2009096859 entitled “A Device For Treating Obesity,”International Publication No. WO2006034400 entitled “Responsive GastricStimulator,” International Publication No. WO2006049725 entitled“Surgical Systems And Devices To Enhance Gastric Restriction Therapies,”U.S. Pat. Pub. No. 2006/0020298 entitled “Systems and Methods forCurbing Appetite,” U.S. Pat. Pub. No. 2004/0147816 entitled “Analysis OfEating Habits,” and International Publication No. WO0226101 entitled“System And Method For The Control Of Behavioral Disorders,”respectively.

GLP-1 Release Stimulation

The controlled device 108 can be configured to apply mechanical orelectrical stimulation to stimulate the release of GLP-1 through L-cellsin the small intestines, e.g., to treat type 2 diabetes. Exemplarydevices and methods for stimulating GLP-1 release are disclosed inInternational Application Nos. PCT/EP2012/055795, PCT/EP2012/055834,PCT/EP2012/055798, PCT/EP2012/055844, and PCT/EP2012/055831. It will beappreciated that any of the devices or methods disclosed in theforegoing references can be modified in accordance with the teachingsherein to stimulate GLP-1 release in response to meal intake detected bythe computer system 106.

Brown Adipose Tissue Activation (Bat)

The controlled device 108 can be configured to activate brown adiposetissue, for example using electrical stimulation as disclosed in U.S.Pat. Pub. No. 2011/0270360, filed on Dec. 29, 2010 entitled “Methods AndDevices For Activating Brown Adipose Tissue Using Electrical Energy.”The meal detection system 100 can trigger BAT activation immediatelyafter a meal when calories are readily available for consumption in theblood stream, which can improve the effectiveness of the BAT activation.Linking treatment to meal intake can also minimize overall stimulationtime, prolonging battery life, allowing for smaller devices, anddelaying the body's adaptation to the therapy.

Gastric Bands

The controlled device 108 can be a gastric band or a device configuredto adjust a gastric band. Adjustable gastric band devices and relatedmethods are disclosed in U.S. Pat. Pub. No. 2009/0204132, filed on Feb.12, 2008 entitled “Automatically Adjusting Band System.” It will beappreciated that any of the devices or methods disclosed in theforegoing reference can be modified in accordance with the teachingsherein to adjust a gastric band based on meal intake detected by thecomputer system 106, e.g., to tighten the band or increase therestriction provided by the band when meal intake is detected or whenmeal intake that exceeds a particular volume or duration threshold isdetected.

Gastric Pacing

The controlled device 108 can be configured to control the tonalcontractions of the stomach to affect one or more physiologicalparameters. For example, the tonal contractions can be controlled tospeed up or slow down gastric emptying, or to induce nausea, satiety,and the like. Exemplary methods and devices for gastric pacing aredisclosed in U.S. Pat. No. 8,239,027, issued on Aug. 7, 2012 entitled“Responsive Gastric Stimulator.” It will be appreciated that any of thedevices or methods disclosed in the foregoing reference can be modifiedin accordance with the teachings herein to adjust the gastric pacingbased on meal intake detected by the computer system 106.

Gastric Space Occupying Devices

The controlled device 108 can be a gastric space and/or volume occupyingdevice (e.g., a gastric balloon) or a device configured to adjust agastric space and/or volume occupying device. Adjustable gastricballoons and related methods are disclosed in U.S. Pat. No. 8,236,023issued on Aug. 7, 2012 entitled “Apparatus And Method For VolumeAdjustment Of Intragastric Balloons.” It will be appreciated that any ofthe devices or methods disclosed in the foregoing reference can bemodified in accordance with the teachings herein to adjust a gastricspace occupying device based on meal intake detected by the computersystem 106, e.g., to increase the volume of the device when meal intakeis detected or when meal intake that exceeds a particular volume orduration threshold is detected.

Gastric Emptying

A number of methods and devices have been developed for changing therate of gastric emptying in a user. Exemplary methods and devices foraltering gastric emptying rates include pyloric shuttles, pyloricvalves, and electrical stimulation devices for altering pyloricfunction. Pyloric shuttles are disclosed in U.S. Pat. No. 8,048,169issued on Nov. 1, 2011 entitled “Pyloric valve obstructing devices andmethods.” Pyloric valves are disclosed in U.S. Pat. No. 8,182,442 issuedon May 22, 2012 entitled “Pyloric valve devices and methods” and in U.S.Publication No. 2012/0259427 filed on Jun. 22, 2012 entitled “PyloricValve.” Electrical stimulation devices for altering pyloric function aredisclosed in International Publication No. WO/2005/041749. Additionaldetails on gastric emptying can be found in Melissa, J, Leventi, A,Klinaki, I, et al. “Alterations of global gastrointestinal motilityafter sleeve gastrectomy: A prospective study.” Ann Surg 2012. It willbe appreciated that any of the devices or methods disclosed in theforegoing references can be modified in accordance with the teachingsherein to adjust a rate of gastric emptying based on meal intakedetected by the computer system 106, e.g., to increase or decrease therate of gastric emptying when meal intake is detected or when mealintake that exceeds a particular volume or duration threshold isdetected

Pattern Recording and Recognition

The controlled device 108 can be configured to record and analyze mealintake patterns and/or issue user reminders. For example, each time thecomputer system 106 detects that meal intake is occurring, thecontrolled device 108 can remind the user to test blood glucose. By wayof further example, the controlled device 108 can store a record of themeal intake event. The record can include various information, includingthe date and time at which meal intake occurred, the sensor data at thetime of meal intake (e.g., the user's heart rate, temperature, etc.),the time duration of the meal intake event, the estimated volume of themeal intake event, and so forth.

The controlled device 108 can use stored records of meal intake eventsto issue alerts to the user that a threshold amount of meal intake hasbeen exceeded, or that a deviation from a meal intake routine hasoccurred. In insulin-dependent users, for example, following a certaindiscipline or meal intake pattern in the user's daily lifestyle can helpkeep the user's condition under control. Stress, travel, and otherthings, however, can lead to deviations from this pattern, in which casethe controlled device 108 can be configured to alert the user to thedeviation (e.g., by emitting a visible or audible alert). A savedhistory of meal intake events can also be helpful in cases wherehyperglycaemia or hypoglycaemia occur, as the user can review their mealintake history on the controlled device 108 to understand what wentwrong. Less-independent insulin users can also benefit from meal intakelogging, as their caregivers can review and monitor the user's mealintake patterns. In highly-dependent insulin patients (e.g., children)the controlled device 108 can be configured to send an email, textmessage, or other alert to the patient's caretaker (e.g., parents) whocan in turn reinforce timely glucose metering and, if necessary, insulinadministration (e.g., by sending instructions or a reminder to the childat school). Generally speaking, meal intake logging and monitoring canprovide the user with increased awareness of their meal intake patterns,which can be helpful in treating various conditions including obesityand diabetes.

The controlled device 108 can also be configured to remind the user totest blood glucose levels, or to provide some other alert, when thecomputer system 106 detects that exercise has occurred or is occurring(e.g., by detecting an elevated heart rate from the ECG sensor oraccelerometer data indicative of exercise).

Combinations

It will be appreciated that the controlled device 108 can be configuredto perform a combination of any of the functions described above, and/orto deliver a combination of the therapies described above. For example,the controlled device 108 can be configured to deliver both a nutrientand electrical stimulation to the user. As described in further detailin U.S. Pat. Pub. No. 2010/0056948 filed Aug. 25, 2009 entitled“Stimulation Of Satiety Hormone Release,” delivering a nutrient to auser and electrically stimulating the user can cause a higher expressionof Glucagon-Like Peptide (GLP-1), and hence enhance triggering of ilealbrake, than delivery of the nutrient to the user without electricalstimulation. By triggering delivery of the nutrient and the electricalstimulation relatively quickly after meal intake begins through thetriggering of the controlled device 108 by the computer system 106,ileal brake can be further encouraged in a faster fashion than wouldnaturally occur or that would occur if the nutrient was deliveredwithout electrical stimulation. In an exemplary embodiment, and asfurther discussed in U.S. Pat. Pub. No. 2010/0056948, the electricalsignal can be delivered to a tissue of the user contemporaneously withthe contacting of L-cells of the tissue with the nutrient delivered tothe user. “Contemporaneously” generally means that during at least partof the time that the electrical signal is being delivered to the tissue,the L-cells are in direct contact with the nutrient. Thus, if theelectrical signal is delivered for a total duration of one second,contacting the L-cells with the nutrient stimulus for 5 seconds afterthe application of the electrical signal and for 0.1 seconds during theapplication of the electrical signal will be considered to have beencontemporaneous with the application of the electrical signal.

In some embodiments, a nutrient can be orally administered to a user,e.g., the user can swallow a nutrient, e.g., as a pill, a fluid, etc.,in conjunction with meal intake, e.g., at a start of a meal. Stimulationof the user's L-Cells can be enhanced by electrical stimulation of theuser in the presence of the nutrient, e.g., by the controlled device 108delivering an electrical signal to the user. In other embodiments, ameal that a user ingests can serve as a stimulus for the user's L-Cells,which can be amplified by triggered delivery of electrical stimulationto the user. Since meals can serve to stimulate L-cell production ofGLP-1, when properly timed, the electrical stimulation can begin as themeal transits into the user's duodenum. There is a feed forward signalto the ileum which is responsible for increase in GLP-1 production. Thiscan be enhanced by the presence of electrical stimulation in theintestine.

CONCLUDING REMARKS

The devices disclosed herein can be designed to be disposed of after asingle use, or they can be designed to be used multiple times. In eithercase, however, the device can be reconditioned for reuse after at leastone use. Reconditioning can include any combination of the steps ofdisassembly of the device, followed by cleaning or replacement ofparticular pieces, and subsequent reassembly. In particular, the devicecan be disassembled, and any number of the particular pieces or parts ofthe device can be selectively replaced or removed in any combination,e.g., electrodes, a battery or other power source, an externallywearable sensor and/or housing therefor, etc. Upon cleaning and/orreplacement of particular parts, the device can be reassembled forsubsequent use either at a reconditioning facility, or by a surgicalteam immediately prior to a surgical procedure. Those skilled in the artwill appreciate that reconditioning of a device can utilize a variety oftechniques for disassembly, cleaning/replacement, and reassembly. Use ofsuch techniques, and the resulting reconditioned device, are all withinthe scope of the present application.

In some embodiments, devices described herein can be processed beforesurgery. First, a new or used instrument is obtained and if necessarycleaned. The instrument can then be sterilized. In one sterilizationtechnique, the instrument is placed in a closed and sealed container,such as a plastic or TYVEK bag. The container and instrument are thenplaced in a field of radiation that can penetrate the container, such asgamma radiation, x-rays, or high-energy electrons. The radiation killsbacteria on the instrument and in the container. The sterilizedinstrument can then be stored in the sterile container. The sealedcontainer keeps the instrument sterile until it is opened in the medicalfacility.

One skilled in the art will appreciate further features and advantagesof the invention based on the above-described embodiments. Accordingly,the invention is not to be limited by what has been particularly shownand described, except as indicated by the appended claims. Allpublications and references cited herein are expressly incorporatedherein by reference in their entirety.

What is claimed is:
 1. A meal detection system, comprising: a pluralityof sensors, each configured to sense a different physiological parameterof a user, the plurality of sensors being disposed external to the user;and a processor in communication with the plurality of sensors andconfigured to analyze outputs of the plurality of sensors to detect mealintake by the user, the processor being further configured to trigger acontrolled device to deliver a therapy to the user in response to mealintake detected by the processor.
 2. The system of claim 1, wherein theplurality of sensors are of different types.
 3. The system of claim 1,wherein, for each of the plurality of sensors, the processor isconfigured to calculate an index based on the output of the sensor andto determine that meal intake occurred when the index exceeds athreshold value.
 4. The system of claim 3, wherein the processor isconfigured to calculate the threshold value by processing a set oftraining data using an average harmonic mean algorithm, the trainingdata including sensor data for at least one user and ground truth datafor the at least one user.
 5. The system of claim 3, wherein theplurality of sensors includes an electromyograph configured to detectelectrical activity of a muscle of the user and wherein the processor isconfigured to calculate an electromyograph index based on a number ofpeaks detected in the electromyograph output.
 6. The system of claim 3,wherein the plurality of sensors includes a microphone configured todetect sounds emitted by the user and wherein the processor isconfigured to calculate a microphone index based on frequency matchingand temporal matching of the microphone output to a predeterminedpattern.
 7. The system of claim 3, wherein the plurality of sensorsincludes an electrocardiograph configured to detect electrical activityof a heart of the user and wherein the processor is configured tocalculate an electrocardiograph index based on a moving average filteredfirst derivative of the standard deviation of interbeat intervals in theelectrocardiograph output.
 8. The system of claim 3, wherein theplurality of sensors includes a temperature sensor configured to detecta temperature of the user and wherein the processor is configured tocalculate a temperature sensor index based on a ratio of low frequencycomponents of the first derivative of the temperature sensor output tolow frequency components of the standard deviation of the temperaturesensor output.
 9. The system of claim 3, wherein the plurality ofsensors includes an accelerometer configured to detect motion of theuser and wherein the processor is configured to calculate anaccelerometer index based on the total energy of the accelerometeroutput in a frequency band of interest.
 10. The system of claim 3,wherein the plurality of sensors includes an electrogastrographconfigured to detect electrical activity of a digestive system of theuser and wherein the processor is configured to calculate anelectrogastrograph index based on the total energy of theelectrogastrograph output in a frequency band of interest.
 11. Thesystem of claim 3, wherein the plurality of sensors includes animpedance sensor configured to detect an impedance across a portion ofthe user and wherein the processor is configured to calculate animpedance sensor index based on the median energy of the impedancesensor output in a frequency band of interest.
 12. The system of claim1, wherein the plurality of sensors includes an electromyograph and anaccelerometer, and wherein the processor is configured to calculate anelectromyograph index, an electromyograph threshold value, anaccelerometer index, and an accelerometer threshold value, and todetermine that: solid meal intake occurred when the electromyographindex exceeds the electromyograph threshold value; liquid meal intakeoccurred when the electromyograph index does not exceed theelectromyograph threshold value and the accelerometer index exceeds theaccelerometer threshold value; and no meal intake occurred when theelectromyograph index does not exceed the electromyograph thresholdvalue and the accelerometer index does not exceed the accelerometerthreshold value.
 13. The system of claim 1, wherein the plurality ofsensors includes an impedance sensor and an accelerometer, and whereinthe processor is configured to calculate an impedance sensor index, animpedance sensor threshold value, an accelerometer index, and anaccelerometer threshold value, and to determine that: solid meal intakeoccurred when the impedance sensor index exceeds the impedance sensorthreshold value; liquid meal intake occurred when the impedance sensorindex does not exceed the impedance sensor threshold value and theaccelerometer index exceeds the accelerometer threshold value; and nomeal intake occurred when the impedance sensor index does not exceed theimpedance sensor threshold value and the accelerometer index does notexceed the accelerometer threshold value.
 14. The system of claim 1,wherein the plurality of sensors includes an electromyograph and amicrophone, and wherein the processor is configured to calculate anelectromyograph index, an electromyograph threshold value, a microphoneindex, and a microphone threshold value, and to determine that: solidmeal intake occurred when the electromyograph index exceeds theelectromyograph threshold value; liquid meal intake occurred when theelectromyograph index does not exceed the electromyograph thresholdvalue and the microphone index exceeds the microphone threshold value;and no meal intake occurred when the electromyograph index does notexceed the electromyograph threshold value and the microphone index doesnot exceed the microphone threshold value.
 15. The system of claim 1,wherein the plurality of sensors includes an impedance sensor and amicrophone, and wherein the processor is configured to calculate animpedance sensor index, an impedance sensor threshold value, amicrophone index, and a microphone threshold value, and to determinethat: solid meal intake occurred when the impedance sensor index exceedsthe impedance sensor threshold value and the microphone index exceedsthe microphone threshold value; liquid meal intake occurred when theimpedance sensor index does not exceed the impedance sensor thresholdvalue and the microphone index exceeds the microphone threshold value;and no meal intake occurred when the impedance sensor index does notexceed the impedance sensor threshold value and the microphone indexdoes not exceed the microphone threshold value.
 16. The system of claim1, further comprising a controlled device, the controlled device beingconfigured to at least one of: electrically stimulate tissue of theuser; deliver a therapeutic agent to the user; deliver a therapeuticagent configured to provoke a release of one or more hormones fromL-cells of the user to trigger ileal brake in the user; deliver insulinto the user; modulate bile acid levels in the user; modulate gastric pHlevels in the user; induce an aversive response in the user; stimulaterelease of GLP-1 in the user; activate brown adipose tissue in the user;adjust a gastric band implanted in the user; control tonal contractionsof the user's stomach; adjust a size or volume of a gastric spaceoccupying device implanted in the user; modulate gastric emptying in theuser; record a history of the user's meal intake events; and issue analert to the user or to a caregiver of the user when the user's mealintake exceeds a predetermined threshold or deviates from apredetermined pattern.
 17. A medical method, comprising: sensing aplurality of physiological parameters of a user using a plurality ofsensors disposed externally to the user; using a processor incommunication with the plurality of sensors, analyzing outputs of theplurality of sensors to detect meal intake by the user; andautomatically triggering a controlled device to deliver a therapy to theuser in response to meal intake detected by the processor.
 18. Themethod of claim 17, further comprising, for each of the plurality ofsensors, using the processor to calculate an index based on the outputof the sensor and using the processor to determine that meal intakeoccurred when the index exceeds a threshold value.
 19. The method ofclaim 18, further comprising using the processor to calculate thethreshold value by processing a set of training data using an averageharmonic mean algorithm, the training data including sensor data for atleast one user and ground truth data for the at least one user.
 20. Themethod of claim 18, wherein said sensing and said analyzing include atleast one of: detecting electrical activity of a muscle of the userusing an electromyograph and calculating an electromyograph index basedon a number of peaks detected in the electromyograph output; detectingsounds emitted by the user using a microphone and calculating amicrophone index based on frequency matching and temporal matching ofthe microphone output to a predetermined pattern; detecting electricalactivity of a heart of the user using an electrocardiograph andcalculating an electrocardiograph index based on a moving averagefiltered first derivative of the standard deviation of interbeatintervals in the electrocardiograph output; detecting a temperature ofthe user and calculating a temperature sensor index based on a ratio oflow frequency components of the first derivative of the temperaturesensor output to low frequency components of the standard deviation ofthe temperature sensor output; detecting motion of the user using anaccelerometer and calculating an accelerometer index based on the totalenergy of the accelerometer output in a frequency band of interest;detecting electrical activity of a digestive system of the user using anelectrogastrograph and calculating an electrogastrograph index based onthe total energy of the electrogastrograph output in a frequency band ofinterest; and detecting an impedance across a portion of the user usingan impedance sensor and calculating an impedance sensor index based onthe median energy of the impedance sensor output in a frequency band ofinterest.
 21. The method of claim 17, wherein triggering the controlleddevice comprises causing the controlled device to at least one of:electrically stimulate tissue of the user; deliver a therapeutic agentto the user; deliver a therapeutic agent configured to provoke a releaseof one or more hormones from L-cells of the user to trigger ileal brakein the user; deliver insulin to the user; modulate bile acid levels inthe user; modulate gastric pH levels in the user; induce an aversiveresponse in the user; stimulate release of GLP-1 in the user; activatebrown adipose tissue in the user; adjust a gastric band implanted in theuser; control tonal contractions of the user's stomach; adjust a size orvolume of a gastric space occupying device implanted in the user;modulate gastric emptying in the user; record a history of the user'smeal intake events; and issue an alert to the user or to a caregiver ofthe user when the user's meal intake exceeds a predetermined thresholdor deviates from a predetermined pattern.
 22. The method of claim 17,wherein said sensing comprises detecting an impedance across a portionof the user using an impedance sensor having a first current electrode,a second current electrode, a first voltage electrode, and a secondvoltage electrode, and wherein the method further comprises at least oneof: positioning the first current electrode on the user's left trapeziusmuscle, positioning the second current electrode on the user's righttrapezius muscle, positioning the first voltage electrode on the user'schest below the user's left clavicle and about half way between theuser's neck and the user's left shoulder, and positioning the secondvoltage electrode on the user's chest below the user's right clavicleand about half way between the user's neck and the user's rightshoulder; and positioning the first current electrode on the user'schest below the user's left clavicle and about half way between theuser's neck and the user's left shoulder, positioning the second currentelectrode on the user's chest below the user's right clavicle and abouthalf way between the user's neck and the user's right shoulder,positioning the first voltage electrode beneath the first currentelectrode and inward towards the user's sternum, and positioning thesecond voltage electrode beneath second current electrode and inwardtowards the user's sternum.